{"id":8427,"date":"2019-08-12T11:29:26","date_gmt":"2019-08-12T18:29:26","guid":{"rendered":"https:\/\/www.springboard.com\/?p=8427"},"modified":"2023-09-28T00:30:14","modified_gmt":"2023-09-28T07:30:14","slug":"narrow-vs-general-ai","status":"publish","type":"post","link":"https:\/\/www.springboard.com\/blog\/data-science\/narrow-vs-general-ai\/","title":{"rendered":"Narrow vs. General AI: What&#8217;s Next for Artificial Intelligence?"},"content":{"rendered":"\n<p><span style=\"font-weight: 400;\">In 1950, Alan Turing asked, \u201cCan machines think?\u201d<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">At the time, it probably seemed like an outlandish suggestion, but fast-forward almost 70 years, and artificial intelligence can detect diseases, fly drones, translate between languages, recognize emotions, trade stocks, and even beat humans at \u201cJeopardy<\/span>.<span style=\"font-weight: 400;\">\u201d It seems like AI is indeed developing a mind of its own.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Artificial intelligence, a term coined by John McCarthy in 1956, began as a simulation of human intelligence through machines and computer systems.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Today, AI represents a way to process data and reach conclusions faster than humans, leading to more accurate predictions of the future. Google\u2019s director of engineering, Ray Kurzeil, forecasts that machines will reach a human level of intelligence by 2029. Kurzeil also says that by 2045 we will reach technological singularity, a time when artificial intelligence becomes more powerful than humans.&nbsp;<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">This inflection point will lead to a separation between AI as we know it today (also called \u201cnarrow AI\u201d) and a future state of AI (\u201cgeneral AI\u201d) that can apply intelligence to any problem.<\/span><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span style=\"font-weight: 400;\">What Is Narrow AI?<\/span><\/h2>\n\n\n\n<p><a href=\"https:\/\/www.techopedia.com\/definition\/32874\/narrow-artificial-intelligence-narrow-ai\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Narrow AI<\/span><\/a><span style=\"font-weight: 400;\"> (ANI) is defined as \u201c<\/span><span style=\"font-weight: 400;\">a specific type of artificial intelligence in which a technology outperforms humans in some very narrowly defined task. Unlike general artificial intelligence, narrow artificial intelligence focuses on a single subset of cognitive abilities and advances in that spectrum.\u201d&nbsp;<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">There are many examples of narrow AI around us every day, represented by devices like Alexa, Google Assistant, Siri, and Cortana. They include:<\/span><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><span style=\"font-weight: 400;\">Self-driving cars<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Facial recognition tools that tag you in pictures<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Customer service bots that redirect inquiries on a webpage<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Google\u2019s page-ranking technology that determines which websites appear at the top of the search engine<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Recommendation systems showing items that could be useful additions to your shopping cart based on browsing history<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Spam filters that keep your inbox clean through automated sorting<\/span><\/li>\n<\/ul>\n\n\n\n<p><span style=\"font-weight: 400;\">Today, many companies are investing in and implementing ANI to improve efficiency, cut costs, and automate tasks; however, ANI has serious limitations. Here are some of the barriers to ANI:<\/span><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><span style=\"font-weight: 400;\">ANI needs a large amount of high-quality data to yield accurate results, and not all environments meet these data requirements.<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">The <\/span><a href=\"https:\/\/www.hatchbuck.com\/blog\/pitfalls-of-ai-technology-no-one-talking-about\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">learning curve to institutionalize AI properly can be steep<\/span><\/a><span style=\"font-weight: 400;\">. Companies have to set up and train their staff on new processes and technologies.<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">If a task changes, the effectiveness of an ANI system decreases, since it is programmed for a specific purpose.<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Sometimes, replacing humans with rules-based machines leads to greater frustration and lowers customer satisfaction\u2014for example, in the hospitality industry, where guests value personalized service and human interaction.&nbsp;<\/span><\/li>\n<\/ul>\n\n\n\n<p><span style=\"font-weight: 400;\">As we address these obstacles and open up new use cases for AI, we are moving toward a new paradigm\u2014that of general artificial intelligence.<\/span><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span style=\"font-weight: 400;\">What Is General AI?<\/span><\/h2>\n\n\n\n<p><span style=\"font-weight: 400;\">Think of R2-D2 in \u201cStar Wars\u201d or Jarvis in \u201cIron Man\u201d and you\u2019ll get a sneak peek into what researchers are labeling as the future of artificial general intelligence (AGI). AGI recently received a $1 billion investment from Microsoft through <\/span><a href=\"https:\/\/openai.com\/blog\/microsoft\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">OpenAI<\/span><\/a><span style=\"font-weight: 400;\">.&nbsp;<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">But what exactly is AGI?<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">AGI, or \u201cstrong AI,\u201d allows a machine to apply knowledge and skills in different contexts. This more closely mirrors human intelligence by providing opportunities for autonomous learning and problem-solving.&nbsp;<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">The challenge now is to move from ANI to AGI in advanced fields like computer vision and natural language processing.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">To reach AGI, computer hardware needs to increase in computational power to perform more total calculations per second (cps). <\/span><a href=\"https:\/\/www.reuters.com\/article\/us-china-supercomputer\/chinas-tianhe-2-retains-top-supercomputer-rank-idUSKCN0J11VV20141117\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Tianhe-2<\/span><\/a><span style=\"font-weight: 400;\">, a supercomputer created by China\u2019s National University of Defense Technology, currently holds the record for cps at 33.86 petaflops (quadrillions of cps). Although that sounds impressive, the <\/span><a href=\"https:\/\/www.scienceabc.com\/humans\/the-human-brain-vs-supercomputers-which-one-wins.html\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">human brain<\/span><\/a><span style=\"font-weight: 400;\"> is estimated to be capable of one exaflop (a billion billion cps). Technology still needs to catch up.&nbsp;<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Currently, one of the main approaches to AGI is called \u201cwhole brain emulation,\u201d where a brain\u2019s memory and mental state are transferred onto a computer. Computer architecture is similar to the brain\u2019s because they can both operate through a system of neurons called neural networks. When the <\/span><a href=\"https:\/\/waitbutwhy.com\/2015\/01\/artificial-intelligence-revolution-1.html\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">right action is taken<\/span><\/a><span style=\"font-weight: 400;\">, it strengthens the transistor connections in the firing pathways. Through trial and error, technology can learn and form smart neural pathways.&nbsp;<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">To date, scientists have been able <\/span><a href=\"https:\/\/www.smithsonianmag.com\/smart-news\/weve-put-worms-mind-lego-robot-body-180953399\/?no-ist\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">to replicate the brain<\/span><\/a> of a 1-millimeter flatworm consisting of 302 neurons<span style=\"font-weight: 400;\">. The human brain, however, is estimated to contain 100 billion neurons, which means we have a ways to go before we can recreate our brain.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Quantum computers, which use quantum mechanics to process exponentially more data than normal computers, are positioned to be the next technological frontier to facilitate AGI.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">For AGI to match human intelligence, it needs to be able to transfer learnings from one environment to another, use common sense, work collaboratively with other machine and human stakeholders, and attain consciousness.&nbsp;<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Neuroscientist <\/span><a href=\"https:\/\/singularityhub.com\/2019\/03\/26\/what-would-it-mean-for-ai-to-become-conscious\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Dr. Heather Berlin<\/span><\/a><span style=\"font-weight: 400;\"> at the Icahn School of Medicine at Mount Sinai defined consciousness in three different ways: \u201cpure subjective experience (\u2018Look, the sky is blue\u2019), awareness of one\u2019s own subjective experience (\u2018Oh, it\u2019s me that\u2019s seeing the blue sky\u2019), and relating one subjective experience to another (\u2018The blue sky reminds me of a blue ocean\u2019).\u201d Developing artificial consciousness requires subjective, conscious experience in addition to pure intellectual horsepower.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Many experts have different predictions about when we will reach AGI. In May 2017, over 350 machine learning and neuroscience experts were surveyed and around <\/span><a href=\"https:\/\/blog.aimultiple.com\/artificial-general-intelligence-singularity-timing\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">50% believed it would happen before 2060<\/span><\/a><span style=\"font-weight: 400;\">. Louis Rosenberg, CEO of the technology company Unanimous AI, predicts that it will happen sooner\u2014around 2030<\/span><span style=\"font-weight: 400;\">\u2014<\/span><span style=\"font-weight: 400;\">and Patrick Winston, MIT professor and former director of the MIT Artificial Intelligence Laboratory, puts the date around 2040.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">With all these forecasts, how will we know when we\u2019ve reached AGI?<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">One of the most famous tests to compare the intelligence of humans and computers is the Turing test, where a human contrasts the conversational abilities of a human and machine. Apple co-founder Steve Wozniak also coined the \u201ccoffee test,\u201d where a machine enters a typical home and figures out how to prepare a cup of coffee. Other tests evaluate whether robots can successfully attend college or replace important job functions with greater efficacy than human workers.<\/span><\/p>\n\n\n<div class=\"bg-leaf-50 p-4 my-3\"><h4 class=\"fw-bold text-center\">Get To Know Other\tData Science Students<\/h4><div class=\"row row-cols-1 row-cols-lg-3\"><div class=\"col\"><div class=\"card success-story-card h-100 d-flex justify-content-between mb-0\"><div class=\"flex-grow-1 text-center\"><a class=\"d-inline-block rounded-circle\" href=\"\/success\/brandon-beidel\" style=\"width:125px;height:125px;overflow:hidden\"><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/res.cloudinary.com\/springboard-images\/image\/upload\/v1635453422\/Brandon_Beidel_125x125.png\" alt=\"Brandon Beidel\" style=\"object-fit:contain;max-width:170px;height:125px\" \/><\/a><p class=\"fw-bold mb-0\">Brandon Beidel<\/p><p class=\"text-muted lh-1\">Senior Data Scientist at Red Ventures<\/p><\/div><div class=\"w-100 d-block d-md-none mt-3\"><\/div><p class=\"mb-0 mx-auto text-center\"><a class=\"btn btn-primary mx-auto\" href=\"\/success\/brandon-beidel\">Read Story<\/a><\/p><\/div><\/div><div class=\"col d-none d-md-block\"><div class=\"card success-story-card h-100 d-flex justify-content-between mb-0\"><div class=\"flex-grow-1 text-center\"><a class=\"d-inline-block rounded-circle\" href=\"\/success\/diana-xie\" style=\"width:125px;height:125px;overflow:hidden\"><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/res.cloudinary.com\/springboard-images\/image\/upload\/v1629203192\/Student%20Success\/Diana_Xie_125x125.png\" alt=\"Diana Xie\" style=\"object-fit:contain;max-width:170px;height:125px\" \/><\/a><p class=\"fw-bold mb-0\">Diana Xie<\/p><p class=\"text-muted lh-1\">Machine Learning Engineer at IQVIA<\/p><\/div><p class=\"mb-0 mx-auto text-center\"><a class=\"btn btn-primary mx-auto\" href=\"\/success\/diana-xie\">Read Story<\/a><\/p><\/div><\/div><div class=\"col d-none d-md-block\"><div class=\"card success-story-card h-100 d-flex justify-content-between mb-0\"><div class=\"flex-grow-1 text-center\"><a class=\"d-inline-block rounded-circle\" href=\"\/success\/cassie-gong\" style=\"width:125px;height:125px;overflow:hidden\"><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/res.cloudinary.com\/springboard-images\/image\/upload\/v1629203193\/Student%20Success\/Cassie_Gong_125x125.png\" alt=\"Mengqin (Cassie) Gong\" style=\"object-fit:contain;max-width:170px;height:125px\" \/><\/a><p class=\"fw-bold mb-0\">Mengqin (Cassie) Gong<\/p><p class=\"text-muted lh-1\">Data Scientist at Whatsapp<\/p><\/div><p class=\"mb-0 mx-auto text-center\"><a class=\"btn btn-primary mx-auto\" href=\"\/success\/cassie-gong\">Read Story<\/a><\/p><\/div><\/div><\/div><\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><span style=\"font-weight: 400;\">Machine Learning and Deep Learning on the Road to AGI<\/span><\/h2>\n\n\n\n<p><span style=\"font-weight: 400;\">So how does other <a href=\"https:\/\/www.springboard.com\/blog\/data-science\/machine-learning-terminology\/\" target=\"_blank\" data-type=\"URL\" data-id=\"https:\/\/www.springboard.com\/blog\/data-science\/machine-learning-terminology\/\" rel=\"noreferrer noopener\">AI terminology<\/a> fit into the new model of ANI and AGI?<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Machine learning describes the ability to find patterns and make decisions without instructions or pre-programming, the ability for computer systems to truly \u201clearn\u201d on their own. Machine learning therefore comprises a subset of AI, but not the other way around.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\"><a href=\"https:\/\/www.springboard.com\/blog\/data-science\/artificial-intelligence-vs-machine-learning-vs-deep-learning\/\" target=\"_blank\" data-type=\"URL\" data-id=\"https:\/\/www.springboard.com\/blog\/data-science\/artificial-intelligence-vs-machine-learning-vs-deep-learning\/\" rel=\"noreferrer noopener\">Deep learning<\/a> is a subset of machine learning that \u201clearns\u201d from unsupervised and unstructured data that is processed through neural networks, algorithms with brain-like functions.&nbsp;<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Neural networks can develop through both training and inference. Training involves using different algorithms and improving on them over time while incorporating new data sources. Inference means that a machine can identify which data sources it needs to make a prediction through logical rules and deductive reasoning.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Research progress in machine learning and deep learning is facilitating the transition from ANI to AGI by enabling decision-making without explicit instructions.<\/span><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span style=\"font-weight: 400;\">Toward Artificial Super-Intelligence (ASI)<\/span><\/h2>\n\n\n\n<p><span style=\"font-weight: 400;\">Artificial super-intelligence (ASI) is a step further from AGI, where artificial intelligence exceeds human capabilities to operate at a genius level. Since ASI is still hypothetical, there are no real limits to what ASI could accomplish, from building nanotechnology to producing objects to preventing aging.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Many philosophers and scientists have different theories about the feasibility of reaching ASI. Cognitive scientist <\/span><a href=\"http:\/\/consc.net\/papers\/singularity.pdf\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">David Chalmer<\/span><\/a><span style=\"font-weight: 400;\"> believes that once AGI is achieved, it will be relatively straightforward to extend capabilities and efficiency to attain ASI. According to Moore\u2019s law, computational power should double at least every two years, which suggests there may not be a limit to technology\u2019s eventual power.&nbsp;<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">One of the <\/span><a href=\"https:\/\/medium.com\/swlh\/the-road-to-artificial-super-intelligence-6811e222e256\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">roadblocks to ASI<\/span><\/a><span style=\"font-weight: 400;\"> is the complexity of global problems. Can machines really solve world hunger or stop climate change? Additionally, ASI will need an exceptional amount of data, even relative to AGI. Some believe that using genetic engineering to create a super-intelligent group of humans is the best bet at ASI, while others posit that ASI will involve a new generation of supercomputers.<\/span><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span style=\"font-weight: 400;\">The Future of AI<\/span><\/h2>\n\n\n\n<p><span style=\"font-weight: 400;\">Although we still have a long way to go before AGI and ASI, AI is moving quickly, with new discoveries and milestones emerging all the time with the combination of <a href=\"https:\/\/www.springboard.com\/blog\/data-science\/data-science-definition\/\">data science<\/a>. Relative to human intelligence, AI holds promise for being able to multitask, perfectly recall and memorize information, function continuously without breaks, make calculations at record speed, sift through lengthy records and documents, and make unbiased decisions with the assistance of programmers, <a href=\"https:\/\/www.springboard.com\/blog\/data-science\/what-does-a-data-scientist-do\/\" data-type=\"post\" data-id=\"24427\">data scientists<\/a>, machine learning engineers, and deep learning researchers.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Recently, Google\u2019s AlphaZero <\/span><a href=\"https:\/\/www.chess.com\/news\/view\/google-s-alphazero-destroys-stockfish-in-100-game-match\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">won a 100-game chess championship<\/span><\/a><span style=\"font-weight: 400;\"> through reinforcement learning and IBM created robots that can provide <\/span><a href=\"https:\/\/www.nbcnews.com\/mach\/tech\/new-ibm-robot-holds-its-own-debate-human-ncna884536\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">formidable competition in world-class debate competitions<\/span><\/a><span style=\"font-weight: 400;\">.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">As AI continues to take over more jobs, there are big debates over the ethics of AI and whether governments should step in to monitor and regulate growth. AI could transform human relationships, <\/span><a href=\"https:\/\/www.forbes.com\/sites\/bernardmarr\/2018\/11\/19\/is-artificial-intelligence-dangerous-6-ai-risks-everyone-should-know-about\/#5f662b2d2404\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">increase discrimination<\/span><\/a><span style=\"font-weight: 400;\">, invade personal privacy, pose security threats through autonomous weapons, and even, in some doomsday scenarios, end <\/span><a href=\"https:\/\/www.quantumrun.com\/prediction\/will-artificial-superintelligence-exterminate-humanity-future\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">humanity<\/span><\/a><span style=\"font-weight: 400;\"> as we know it.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">These issues may sound daunting, but they also make the study of AI all the more intriguing and impactful.&nbsp;<\/span><\/p>\n\n\n\n<p>Companies are no longer just collecting data. They\u2019re seeking to use it to outpace competitors, especially with the rise of AI and advanced analytics techniques. Between organizations and these techniques are the data scientists \u2013 the experts who crunch numbers and translate them into actionable strategies. The future, it seems, belongs to those who can decipher the story hidden within the data, making the role of data scientists more important than ever.<\/p>\n\n\n\n<p>In this article, we\u2019ll look at 13 careers in data science, analyzing the roles and responsibilities and how to land that specific job in the best way. Whether you\u2019re more drawn out to the creative side or interested in the strategy planning part of data architecture, there\u2019s a niche for you.&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Is Data Science A Good Career?<\/h2>\n\n\n\n<p>Yes. Besides being a field that comes with competitive salaries, the demand for data scientists continues to increase as they have an enormous impact on their organizations. It\u2019s an interdisciplinary field that keeps the work varied and interesting.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">10 Data Science Careers To Consider<\/h2>\n\n\n\n<p>Whether you want to change careers or land your first job in the field, here are 13 of the most lucrative data science careers to consider.<\/p>\n\n\n\n<div class=\"wp-block-essential-blocks-pro-data-table\"><div class=\"eb-parent-wrapper eb-parent-eb-data-table-cabj7 \"><div class=\"eb-data-table-cabj7 eb-data-table-wrapper\"><div class=\"eb-data-table-wrapper-inner\" data-post-id=\"13385\" data-block-id=\"eb-data-table-cabj7\" data-hide-header=\"false\" data-fixed-header=\"false\" data-show-pagination=\"false\" data-show-search=\"false\" data-fixed-header-scroll-height=\"300\"><\/div><\/div><\/div><\/div>\n\n\n\n<p><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Data Scientist<\/h3>\n\n\n\n<p>Data scientists represent the foundation of the data science department. At the core of their role is the ability to analyze and interpret complex digital data, such as usage statistics, sales figures, logistics, or market research \u2013 all depending on the field they operate in.<\/p>\n\n\n\n<p>They combine their computer science, statistics, and mathematics expertise to process and model data, then interpret the outcomes to create actionable plans for companies.&nbsp;<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">General Requirements<\/h4>\n\n\n\n<p>A data scientist\u2019s career starts with a solid mathematical foundation, whether it\u2019s interpreting the results of an A\/B test or optimizing a marketing campaign. Data scientists should have programming expertise (primarily in Python and R) and strong data manipulation skills.&nbsp;<\/p>\n\n\n\n<p>Although a university degree is not always required beyond their on-the-job experience, data scientists need a bunch of <a href=\"https:\/\/www.springboard.com\/blog\/data-science\/best-data-science-courses\/\">data science courses<\/a> and certifications that demonstrate their expertise and willingness to learn.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Average Salary<\/h4>\n\n\n\n<p>The average salary of a data scientist in the US is <a href=\"https:\/\/www.glassdoor.com\/Salaries\/data-scientist-salary-SRCH_KO0,14.htm\" target=\"_blank\" rel=\"noopener\">$156,363<\/a> per year.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Data Analyst<\/h3>\n\n\n\n<p>A data analyst explores the nitty-gritty of data to uncover patterns, trends, and insights that are not always immediately apparent. They collect, process, and perform statistical analysis on large datasets and translate numbers and data to inform business decisions.<\/p>\n\n\n\n<p>A typical day in their life can involve using tools like Excel or SQL and more advanced reporting tools like Power BI or Tableau to create dashboards and reports or visualize data for stakeholders. With that in mind, they have a unique skill set that allows them to act as a bridge between an organization&#8217;s technical and business sides.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">General Requirements<\/h4>\n\n\n\n<p>To become a data analyst, you should have basic programming skills and proficiency in several data analysis tools. A lot of data analysts turn to specialized courses or <a href=\"https:\/\/www.springboard.com\/blog\/data-science\/best-data-science-bootcamps\/\">data science bootcamps<\/a> to acquire these skills.&nbsp;<\/p>\n\n\n\n<p>For example, Coursera offers courses like Google&#8217;s Data Analytics Professional Certificate or IBM&#8217;s Data Analyst Professional Certificate, which are well-regarded in the industry. A bachelor&#8217;s degree in fields like computer science, statistics, or economics is standard, but many data analysts also come from diverse backgrounds like business, finance, or even social sciences.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Average Salary<\/h4>\n\n\n\n<p>The average base salary of a data analyst is <a href=\"https:\/\/www.indeed.com\/career\/data-analyst\/salaries\" target=\"_blank\" rel=\"noopener\">$76,892<\/a> per year.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Business Analyst<\/h3>\n\n\n\n<p>Business analysts often have an essential role in an organization, driving change and improvement. That\u2019s because their main role is to understand business challenges and needs and translate them into solutions through data analysis, process improvement, or resource allocation.&nbsp;<\/p>\n\n\n\n<p>A typical day as a business analyst involves conducting market analysis, assessing business processes, or developing strategies to address areas of improvement. They use a variety of tools and methodologies, like SWOT analysis, to evaluate business models and their integration with technology.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">General Requirements<\/h4>\n\n\n\n<p>Business analysts often have related degrees, such as BAs in Business Administration, Computer Science, or IT. Some roles might require or favor a master\u2019s degree, especially in more complex industries or corporate environments.<\/p>\n\n\n\n<p>Employers also value a business analyst\u2019s knowledge of project management principles like Agile or Scrum and the ability to think critically and make well-informed decisions.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Average Salary<\/h4>\n\n\n\n<p>A business analyst can earn an average of <a href=\"https:\/\/www.indeed.com\/career\/business-analyst\/salaries\" target=\"_blank\" rel=\"noopener\">$84,435<\/a> per year.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Database Administrator<\/h3>\n\n\n\n<p>The role of a database administrator is multifaceted. Their responsibilities include managing an organization&#8217;s database servers and application tools.&nbsp;<\/p>\n\n\n\n<p>A DBA manages, backs up, and secures the data, making sure the database is available to all the necessary users and is performing correctly. They are also responsible for setting up user accounts and regulating access to the database. DBAs need to stay updated with the latest trends in database management and seek ways to improve database performance and capacity. As such, they collaborate closely with IT and database programmers.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">General Requirements<\/h4>\n\n\n\n<p>Becoming a database administrator typically requires a solid educational foundation, such as a BA degree in data science-related fields. Nonetheless, it\u2019s not all about the degree because real-world skills matter a lot. Aspiring database administrators should learn database languages, with SQL being the key player. They should also get their hands dirty with popular database systems like Oracle and Microsoft SQL Server.&nbsp;<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Average Salary<\/h4>\n\n\n\n<p>Database administrators earn an average salary of <a href=\"https:\/\/www.indeed.com\/career\/database-administrator\/salaries\" target=\"_blank\" rel=\"noopener\">$77,391<\/a> annually.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Data Engineer<\/h3>\n\n\n\n<p>Successful data engineers construct and maintain the infrastructure that allows the data to flow seamlessly. Besides understanding data ecosystems on the day-to-day, they build and oversee the pipelines that gather data from various sources so as to make data more accessible for those who need to analyze it (e.g., data analysts).<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">General Requirements<\/h4>\n\n\n\n<p>Data engineering is a role that demands not just technical expertise in tools like SQL, Python, and Hadoop but also a creative problem-solving approach to tackle the complex challenges of managing massive amounts of data efficiently.&nbsp;<\/p>\n\n\n\n<p>Usually, employers look for credentials like university degrees or advanced data science courses and bootcamps.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Average Salary<\/h4>\n\n\n\n<p>Data engineers earn a whooping average salary of <a href=\"https:\/\/www.glassdoor.com\/Salaries\/data-engineer-salary-SRCH_KO0,13.htm\" target=\"_blank\" rel=\"noopener\">$125,180<\/a> per year.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Database Architect<\/h3>\n\n\n\n<p>A database architect\u2019s main responsibility involves designing the entire blueprint of a data management system, much like an architect who sketches the plan for a building. They lay down the groundwork for an efficient and scalable data infrastructure.&nbsp;<\/p>\n\n\n\n<p>Their day-to-day work is a fascinating mix of big-picture thinking and intricate detail management. They decide how to store, consume, integrate, and manage data by different business systems.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">General Requirements<\/h4>\n\n\n\n<p>If you\u2019re aiming to excel as a database architect but don\u2019t necessarily want to pursue a degree, you could start honing your technical skills. Become proficient in database systems like MySQL or Oracle, and learn data modeling tools like ERwin. Don\u2019t forget programming languages &#8211; SQL, Python, or Java.&nbsp;<\/p>\n\n\n\n<p>If you want to take it one step further, pursue a credential like the Certified Data Management Professional (CDMP) or the <a href=\"https:\/\/www.springboard.com\/courses\/data-science-career-track\/\">Data Science Bootcamp by Springboard<\/a>.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Average Salary<\/h4>\n\n\n\n<p>Data architecture is a very lucrative career. A database architect can earn an average of <a href=\"https:\/\/www.glassdoor.com\/Salaries\/data-architect-salary-SRCH_KO0,14.htm\" target=\"_blank\" rel=\"noopener\">$165,383<\/a> per year.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Machine Learning Engineer<\/h3>\n\n\n\n<p>A machine learning engineer experiments with various machine learning models and algorithms, fine-tuning them for specific tasks like image recognition, natural language processing, or predictive analytics. Machine learning engineers also collaborate closely with data scientists and analysts to understand the requirements and limitations of data and translate these insights into solutions.&nbsp;<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">General Requirements<\/h4>\n\n\n\n<p>As a rule of thumb, machine learning engineers must be proficient in programming languages like Python or Java, and be familiar with machine learning frameworks like TensorFlow or PyTorch. To successfully pursue this career, you can either choose to undergo a degree or enroll in courses and follow a self-study approach.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Average Salary<\/h4>\n\n\n\n<p>Depending heavily on the company&#8217;s size, machine learning engineers can earn between <a href=\"https:\/\/www.glassdoor.com\/Salaries\/machine-learning-engineer-salary-SRCH_KO0,25.htm\" target=\"_blank\" rel=\"noopener\">$125K and $187K<\/a> per year, one of the <a href=\"https:\/\/www.springboard.com\/blog\/data-science\/careers-in-ai\/\">highest-paying AI careers<\/a>.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Quantitative Analyst<\/h3>\n\n\n\n<p>Qualitative analysts are essential for financial institutions, where they apply mathematical and statistical methods to analyze financial markets and assess risks. They are the brains behind complex models that predict market trends, evaluate investment strategies, and assist in making informed financial decisions.&nbsp;<\/p>\n\n\n\n<p>They often deal with derivatives pricing, algorithmic trading, and risk management strategies, requiring a deep understanding of both finance and mathematics.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">General Requirements<\/h4>\n\n\n\n<p>This data science role demands strong analytical skills, proficiency in mathematics and statistics, and a good grasp of financial theory. It always helps if you come from a finance-related background.&nbsp;<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Average Salary<\/h4>\n\n\n\n<p>A quantitative analyst earns an average of <a href=\"https:\/\/www.glassdoor.com\/Salaries\/quantitative-analyst-salary-SRCH_KO0,20.htm\" target=\"_blank\" rel=\"noopener\">$173,307<\/a> per year.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Data Mining Specialist<\/h3>\n\n\n\n<p>A data mining specialist uses their statistics and machine learning expertise to reveal patterns and insights that can solve problems. They swift through huge amounts of data, applying algorithms and data mining techniques to identify correlations and anomalies. In addition to these, data mining specialists are also essential for organizations to predict future trends and behaviors.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">General Requirements<\/h4>\n\n\n\n<p>If you want to land a career in data mining, you should possess a degree or have a solid background in computer science, statistics, or a related field.&nbsp;<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Average Salary<\/h4>\n\n\n\n<p>Data mining specialists earn <a href=\"https:\/\/www.glassdoor.com\/Salaries\/data-mining-specialist-salary-SRCH_KO0,22.htm\" target=\"_blank\" rel=\"noopener\">$109,023<\/a> per year.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Data Visualisation Engineer<\/h3>\n\n\n\n<p>Data visualisation engineers specialize in transforming data into visually appealing graphical representations, much like a data storyteller. A big part of their day involves working with data analysts and business teams to understand the data\u2019s context.&nbsp;<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">General Requirements<\/h4>\n\n\n\n<p>Data visualization engineers need a strong foundation in data analysis and be proficient in programming languages often used in data visualization, such as JavaScript, Python, or R. A valuable addition to their already-existing experience is a bit of expertise in design principles to allow them to create visualizations.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Average Salary<\/h4>\n\n\n\n<p>The average annual pay of a data visualization engineer is <a href=\"https:\/\/www.glassdoor.com\/Salaries\/data-visualization-engineer-salary-SRCH_KO0,27.htm\" target=\"_blank\" rel=\"noopener\">$103,031<\/a>.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Resources To Find Data Science Jobs<\/h2>\n\n\n\n<p>The key to finding a good data science job is knowing where to look without procrastinating. To make sure you leverage the right platforms, read on.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Job Boards<\/h3>\n\n\n\n<p>When hunting for data science jobs, both niche job boards and general ones can be treasure troves of opportunity.&nbsp;<\/p>\n\n\n\n<p>Niche boards are created specifically for data science and related fields, offering listings that cut through the noise of broader job markets. Meanwhile, general job boards can have hidden gems and opportunities.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Online Communities<\/h3>\n\n\n\n<p>Spend time on platforms like Slack, Discord, GitHub, or IndieHackers, as they are a space to share knowledge, collaborate on projects, and find job openings posted by community members.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Network And LinkedIn<\/h3>\n\n\n\n<p>Don\u2019t forget about socials like LinkedIn or Twitter. The LinkedIn Jobs section, in particular, is a useful resource, offering a wide range of opportunities and the ability to directly reach out to hiring managers or apply for positions. Just make sure not to apply through the \u201cEasy Apply\u201d options, as you\u2019ll be competing with thousands of applicants who bring nothing unique to the table.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">FAQs about Data Science Careers<\/h2>\n\n\n\n<p>We answer your most frequently asked questions.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Do I Need A Degree For Data Science?<\/h3>\n\n\n\n<p>A degree is not a set-in-stone requirement to <a href=\"https:\/\/www.springboard.com\/blog\/data-science\/learn-data-science-without-degree\/\">become a data scientist<\/a>. It\u2019s true many data scientists hold a BA\u2019s or MA\u2019s degree, but these just provide foundational knowledge. It\u2019s up to you to pursue further education through courses or bootcamps or work on projects that enhance your expertise. What matters most is your ability to demonstrate proficiency in data science concepts and tools.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Does Data Science Need Coding?<\/h3>\n\n\n\n<p>Yes. Coding is essential for data manipulation and analysis, especially knowledge of programming languages like Python and R.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Is Data Science A Lot Of Math?<\/h3>\n\n\n\n<p>It depends on the career you want to pursue. Data science involves quite a lot of math, particularly in areas like statistics, probability, and linear algebra.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">What Skills Do You Need To Land an Entry-Level Data Science Position?<\/h3>\n\n\n\n<p>To land an entry-level job in data science, you should be proficient in several areas. As mentioned above, knowledge of programming languages is essential, and you should also have a good understanding of statistical analysis and machine learning. Soft skills are equally valuable, so make sure you\u2019re acing problem-solving, critical thinking, and effective communication.<\/p>\n\n\n\n<p class=\"rm has-background\" style=\"background-color:#efeff6\"><strong>Since you\u2019re here\u2026<\/strong>Are you interested in this career track? Investigate with our free guide to <a href=\"https:\/\/www.springboard.com\/blog\/data-science\/what-does-a-data-scientist-do\/\" data-type=\"post\" data-id=\"24427\">what a data professional <em>actually<\/em> does<\/a>. When you\u2019re ready to build a CV that will make hiring managers melt, join our <a href=\"https:\/\/www.springboard.com\/courses\/data-science-career-track\/\" data-type=\"URL\" data-id=\"https:\/\/www.springboard.com\/courses\/data-science-career-track\/\" target=\"_blank\" rel=\"noreferrer noopener\">Data Science Bootcamp<\/a> which will help you land a job or your tuition back!<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In 1950, Alan Turing asked, \u201cCan machines think?\u201d At the time, it probably seemed like an outlandish suggestion, but fast-forward almost 70 years, and artificial intelligence can detect diseases, fly drones, translate between languages, recognize emotions, trade stocks, and even beat humans at \u201cJeopardy.\u201d It seems like AI is indeed developing a mind of its [&hellip;]<\/p>\n","protected":false},"author":66,"featured_media":8510,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_eb_attr":"","_eb_data_table":"","footnotes":""},"categories":[67],"tags":[],"marketing_tags":[1466],"class_list":{"0":"post-8427","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-data-science"},"acf":[],"_links":{"self":[{"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/posts\/8427"}],"collection":[{"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/users\/66"}],"replies":[{"embeddable":true,"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/comments?post=8427"}],"version-history":[{"count":4,"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/posts\/8427\/revisions"}],"predecessor-version":[{"id":50112,"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/posts\/8427\/revisions\/50112"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/media\/8510"}],"wp:attachment":[{"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/media?parent=8427"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/categories?post=8427"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/tags?post=8427"},{"taxonomy":"marketing_tags","embeddable":true,"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/marketing_tags?post=8427"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}