{"id":5767,"date":"2019-01-03T05:35:43","date_gmt":"2019-01-03T13:35:43","guid":{"rendered":"https:\/\/www.springboard.com\/?p=5767"},"modified":"2023-08-18T07:47:26","modified_gmt":"2023-08-18T14:47:26","slug":"machine-learning-engineer-vs-data-scientist","status":"publish","type":"post","link":"https:\/\/www.springboard.com\/blog\/data-science\/machine-learning-engineer-vs-data-scientist\/","title":{"rendered":"Machine Learning Engineer vs. Data Scientist"},"content":{"rendered":"\n<p><span style=\"font-weight: 400;\">There\u2019s some confusion surrounding the roles of machine learning engineer vs. data scientist, primarily because they are both relatively new. However, if you parse things out and examine the semantics, the distinctions become clear.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">At a high level, we&#8217;re talking about scientists and engineers. While a scientist needs to fully understand the, well, science behind their work, an engineer is tasked with building something.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">But before we go any further, let\u2019s address the <\/span><b>difference between machine learning and data science<\/b><span style=\"font-weight: 400;\">. <\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">It starts with having a solid definition of <\/span><b>artificial intelligence<\/b><span style=\"font-weight: 400;\">. This term was first coined by John McCarthy in 1956 to discuss and develop the concept of \u201cthinking machines,\u201d which included the following:<\/span><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><span style=\"font-weight: 400;\">Automata theory<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Complex information processing<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Cybernetics <\/span><\/li>\n<\/ul>\n\n\n\n<p><span style=\"font-weight: 400;\">Approximately six decades later, artificial intelligence is now perceived to be a sub-field of computer science where computer systems are developed to perform tasks that would typically demand human intervention. These include:<\/span><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><span style=\"font-weight: 400;\">Decision-making<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Speech recognition<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Translation between languages<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Visual perception<\/span><\/li>\n<\/ul>\n\n\n\n<p><b>Machine learning<\/b><span style=\"font-weight: 400;\"> is a branch of artificial intelligence where a class of data-driven algorithms enables software applications to become highly accurate in predicting outcomes without any need for explicit programming. <\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">The basic premise here is to develop algorithms that can receive input data and leverage statistical models to predict an output while updating outputs as new data becomes available.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">The processes involved have a lot in common with predictive modeling and data mining. This is because both approaches demand one to search through the data to identify patterns and adjust the program accordingly.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Most of us have experienced machine learning in action in one form or another. If you have shopped on Amazon or watched something on Netflix, those personalized (product or movie) recommendations are machine learning in action.<\/span><\/p>\n\n\n\n<p><b>Data science<\/b><span style=\"font-weight: 400;\"> can be described as the <\/span><a href=\"https:\/\/arxiv.org\/pdf\/1804.10846.pdf\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">description, prediction, and causal inference from both structured and unstructured data<\/span><\/a><span style=\"font-weight: 400;\">. This discipline helps individuals and enterprises make better business decisions.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">It\u2019s also a study of where data originates, what it represents, and how it could be transformed into a valuable resource. To achieve the latter, a massive amount of data has to be mined to identify patterns to help businesses:<\/span><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><span style=\"font-weight: 400;\">Gain a competitive advantage<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Identify new market opportunities<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Increase efficiencies<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Rein in costs<\/span><\/li>\n<\/ul>\n\n\n\n<p><span style=\"font-weight: 400;\">The field of <a href=\"https:\/\/www.springboard.com\/blog\/data-science\/data-science-definition\/\" target=\"_blank\" rel=\"noreferrer noopener\">data science<\/a> employs computer science disciplines like mathematics and statistics and incorporates techniques like data mining, cluster analysis, visualization, and\u2014yes\u2014machine learning.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Having said all of that, this post aims to answer the following questions:<\/span><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><span style=\"font-weight: 400;\">Machine learning engineer vs. data scientist<\/span><span style=\"font-weight: 400;\">: what degree do they need?<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Machine learning engineer vs. data scientist<\/span><span style=\"font-weight: 400;\">: what do they actually do?<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Machine learning engineer vs. data scientist<\/span><span style=\"font-weight: 400;\">: what\u2019s the average salary?<\/span><\/li>\n<\/ul>\n\n\n\n<p><em>If you&#8217;re looking for a more comprehensive insight into machine learning career options, check out our guides on <a href=\"https:\/\/www.springboard.com\/blog\/data-science\/how-to-become-a-data-scientist\/\" target=\"_blank\" data-type=\"URL\" data-id=\"https:\/\/www.springboard.com\/blog\/data-science\/how-to-become-a-data-scientist\/\" rel=\"noreferrer noopener\">how to become a data scientist<\/a> and <a href=\"https:\/\/www.springboard.com\/blog\/data-science\/how-to-become-data-engineer\/\" target=\"_blank\" data-type=\"URL\" data-id=\"https:\/\/www.springboard.com\/blog\/data-science\/how-to-become-data-engineer\/\" rel=\"noreferrer noopener\">how to become a data engineer<\/a>.<\/em><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Machine Learning Engineer vs. Data Scientist: What They Do<\/h2>\n\n\n\n<p><span style=\"font-weight: 400;\">As mentioned above, there are some similarities when it comes to the roles of machine learning engineers and data scientists. <\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">However, if you look at the two roles as members of the same team, a data scientist does the statistical analysis required to determine which machine learning approach to use, then they model the algorithm and prototype it for testing. At that point, a machine learning engineer takes the prototyped model and makes it work in a production environment at scale.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Going back to the scientist vs. engineer split, a machine learning engineer isn&#8217;t necessarily expected to understand the predictive models and their underlying mathematics the way a data scientist is. A machine learning engineer is, however, expected to master the software tools that make these models usable. <\/span><\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><span style=\"font-weight: 400;\">What Does a Machine Learning Engineer Do?<\/span><\/h4>\n\n\n\n<p><span style=\"font-weight: 400;\">Machine learning engineers sit at the intersection of software engineering and data science. <\/span><span style=\"font-weight: 400;\">They leverage big data tools and programming frameworks to ensure that the raw data gathered from data pipelines are redefined as data science models that are ready to scale as needed.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Machine learning engineers feed data into models defined by <a href=\"https:\/\/www.springboard.com\/blog\/data-science\/what-does-a-data-scientist-do\/\" target=\"_blank\" data-type=\"post\" data-id=\"24427\" rel=\"noreferrer noopener\">data scientists<\/a>. They&#8217;re also responsible for taking theoretical data science models and helping scale them out to production-level models that can handle terabytes of real-time data.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Machine learning engineers also build programs that control computers and robots. The algorithms developed by machine learning engineers enable a machine to identify patterns in its own programming data and teach itself to understand commands and even think for itself.<\/span><\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><span style=\"font-weight: 400;\">What Does a Data Scientist Do?<\/span><\/h4>\n\n\n\n<p><span style=\"font-weight: 400;\">When a business needs to answer a question or solve a problem, they turn to a <\/span><a href=\"https:\/\/www.springboard.com\/blog\/data-science\/data-science-process\/\" target=\"_blank\" data-type=\"URL\" data-id=\"https:\/\/www.springboard.com\/blog\/data-science\/data-science-process\/\" rel=\"noreferrer noopener\"><span style=\"font-weight: 400;\">data scientist to gather, process, and derive valuable insights from the data<\/span><\/a><span style=\"font-weight: 400;\">. Whenever data scientists are hired by an organization, they will explore all aspects of the business and develop programs using programming languages like Java to perform robust analytics.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">They will also use online experiments along with other methods to help businesses achieve sustainable growth. Additionally, they can develop personalized data products to help companies better understand themselves and their customers to make better business decisions.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">As previously mentioned, <a href=\"https:\/\/www.springboard.com\/blog\/data-science\/day-in-the-life-of-a-data-scientist\/\" target=\"_blank\" data-type=\"URL\" data-id=\"https:\/\/www.springboard.com\/blog\/data-science\/day-in-the-life-of-a-data-scientist\/\" rel=\"noreferrer noopener\">data scientists focus on the statistical analysis and research<\/a> needed to determine which machine learning approach to use, then they model the algorithm and prototype it for testing.<\/span><\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><span style=\"font-weight: 400;\">What Do the Experts Say?<\/span><\/h4>\n\n\n\n<p><span style=\"font-weight: 400;\">Springboard recently asked two working professionals for their definitions of machine learning engineer vs. data scientist.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Mansha Mahtani, a data scientist at Instagram, said:<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">&#8220;Given both professions are relatively new, there tends to be a little bit of fluidity on how you define what a machine learning engineer is and what a data scientist is. My experience has been that machine learning engineers tend to write production-level code. For example, if you were a machine learning engineer creating a product to give recommendations to the user, you&#8217;d be actually writing live code that would eventually reach your user. The data scientist would be probably part of that process<\/span><span style=\"font-weight: 400;\">\u2014<\/span><span style=\"font-weight: 400;\">maybe helping the machine learning engineer determine what are the features that go into that model<\/span><span style=\"font-weight: 400;\">\u2014<\/span><span style=\"font-weight: 400;\">but usually data scientists tend to be a little bit more ad hoc to drive a business decision as opposed to writing production-level code.&#8221;<\/span><\/p>\n\n\n\n<p><a href=\"https:\/\/www.springboard.com\/blog\/data-science\/real-talk-with-machine-learning-engineers\/\" target=\"_blank\" data-type=\"URL\" data-id=\"https:\/\/www.springboard.com\/blog\/data-science\/real-talk-with-machine-learning-engineers\/\" rel=\"noreferrer noopener\"><span style=\"font-weight: 400;\">Shubhankar Jain<\/span><\/a><span style=\"font-weight: 400;\">, a machine learning engineer at SurveyMonkey, said:<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">&#8220;A data scientist today would primarily be responsible for translating this business problem of, for example, we want to figure out what product we should sell next to our customers if they\u2019ve already bought a product from us. And translating that business problem into more of a technical model and being able to then output a model that can take in a certain set of attributes about a customer and then spit out some sort of result. An ML engineer would probably then take that model that this data scientist developed and integrate it in with the rest of the company\u2019s platform\u2014and that could involve building, say, an API around this model so that it can be served and consumed, and then being able to maintain the integrity and quality of this model so that it continues to serve really accurate predictions.&#8221;<\/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\/sam-fisher\" style=\"width:125px;height:125px;overflow:hidden\"><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/res.cloudinary.com\/springboard-images\/image\/upload\/v1629203194\/Student%20Success\/Sam_Fisher_125x125.png\" alt=\"Sam Fisher\" style=\"object-fit:contain;max-width:170px;height:125px\" \/><\/a><p class=\"fw-bold mb-0\">Sam Fisher<\/p><p class=\"text-muted lh-1\">Data Science Engineer at Stratyfy<\/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\/sam-fisher\">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\/hastings-reeves\" style=\"width:125px;height:125px;overflow:hidden\"><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/res.cloudinary.com\/springboard-images\/image\/upload\/v1648517255\/Student%20Success\/Hastings_Reeves_3.png\" alt=\"Hastings Reeves\" style=\"object-fit:contain;max-width:170px;height:125px\" \/><\/a><p class=\"fw-bold mb-0\">Hastings Reeves<\/p><p class=\"text-muted lh-1\">Business Intelligence Analyst at Velocity Global<\/p><\/div><p class=\"mb-0 mx-auto text-center\"><a class=\"btn btn-primary mx-auto\" href=\"\/success\/hastings-reeves\">Read Story<\/a><\/p><\/div><\/div><\/div><\/div>\n\n\n\n<h2 class=\"wp-block-heading\">Machine Learning Engineer vs. Data Scientist: Role Requirements<\/h2>\n\n\n\n<h4 class=\"wp-block-heading\"><span style=\"font-weight: 400;\">What Are the Requirements for a Machine Learning Engineer?<\/span><\/h4>\n\n\n\n<p><span style=\"font-weight: 400;\">To work as a machine learning engineer, most companies prefer candidates who have a master\u2019s degree in computer science. However, as this field is relatively new and there is a shortage of top tech talent, many employers will be willing to make exceptions.<\/span><\/p>\n\n\n\n<p><em><strong>Related<\/strong>: <a href=\"https:\/\/www.springboard.com\/blog\/data-science\/machine-learning-resume\/\" target=\"_blank\" data-type=\"URL\" data-id=\"https:\/\/www.springboard.com\/blog\/data-science\/machine-learning-resume\/\" rel=\"noreferrer noopener\">How to Build a Strong Machine Learning Resume<\/a><\/em><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">However, to stand a chance, potential candidates need to be familiar with the standard implementation of machine learning algorithms which are freely available through APIs, libraries, and packages (along with the advantages and disadvantages of each approach). <\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">According to a report by <\/span><a href=\"https:\/\/www.ibm.com\/developerworks\/community\/blogs\/jfp\/entry\/What_Language_Is_Best_For_Machine_Learning_And_Data_Science?lang=en\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">IBM<\/span><\/a><span style=\"font-weight: 400;\">, machine learning engineers should know the following programming languages (as listed by rank):<\/span><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><span style=\"font-weight: 400;\">Python<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Java<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">R <\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">C++<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">C<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">JavaScript<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Scala<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Julia<\/span><\/li>\n<\/ul>\n\n\n\n<p><span style=\"font-weight: 400;\">Here\u2019s what you\u2019ll need to get the job, based on current job postings:<\/span><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><span style=\"font-weight: 400;\">Master\u2019s or Ph.D. in computer science, mathematics, or statistics<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Experience working with Java, Python, and R<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Experience with vision processing, deep neural networks, Gaussian processes, and reinforcement learning<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">A solid understanding of both probability and statistics<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">A firm understanding of mathematics (including the role of algorithm theory in machine learning and complex algorithms that are needed to help machines learn and communicate)<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Advanced knowledge of engineering<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Strong analytical skills<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Experience using programming tools like MATLAB <\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Experience working with large amounts of data in a high throughput environment<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Linux SysAdmin skills<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Experience working with distributed systems tools like Etcd, zookeeper, and consul<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Experience working with messaging tools like Kafka, RabbitMQ, and ZeroMQ<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Extensive knowledge of machine learning evaluation metrics and best practices<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Competency with infrastructure as code (for example, Terraform or Cloudformation)<\/span><\/li>\n<\/ul>\n\n\n\n<h4 class=\"wp-block-heading\"><span style=\"font-weight: 400;\">What Are the Requirements for a Data Scientist?<\/span><\/h4>\n\n\n\n<p><span style=\"font-weight: 400;\">Like machine learning engineers, data scientists also need to be highly educated. In fact, many have a master\u2019s degree or a Ph.D. Based on one recent report, most <\/span><a href=\"https:\/\/www.kdnuggets.com\/2014\/11\/9-must-have-skills-data-scientist.html\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">data scientists have an advanced degree<\/span><\/a><span style=\"font-weight: 400;\"> in engineering (16 percent), computer science (19 percent), or mathematics and statistics (32 percent).<\/span><\/p>\n\n\n\n<p><em><strong>Related<\/strong>: <a href=\"https:\/\/www.springboard.com\/blog\/data-science\/how-to-become-a-data-scientist\/\" target=\"_blank\" data-type=\"URL\" data-id=\"https:\/\/www.springboard.com\/blog\/data-science\/how-to-become-a-data-scientist\/\" rel=\"noreferrer noopener\">A Guide to Becoming a Data Scientist<\/a><\/em><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">That being said, according to <\/span><a href=\"https:\/\/www.quora.com\/profile\/Paula-Griffin-1\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Paula Griffin<\/span><\/a><span style=\"font-weight: 400;\">, <\/span><a href=\"https:\/\/www.forbes.com\/sites\/quora\/2017\/05\/08\/do-i-need-an-advanced-degree-to-become-a-data-scientist\/#4bd641c42ebe\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">product manager at Quora<\/span><\/a><span style=\"font-weight: 400;\">, \u201cThere are large swaths of data science that don\u2019t require [advanced degree] research-oriented skills. There\u2019s a huge amount of impact that you can have by leveraging the skills that are better built through industry settings as well.\u201d<\/span><\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/www.springboard.com\/blog\/wp-content\/uploads\/2019\/01\/image1-1024x973.jpg\" alt=\"what it takes to become a data scientist\" class=\"wp-image-5768\"\/><\/figure>\n\n\n\n<p><span style=\"font-weight: 400;\">(<\/span><a href=\"https:\/\/machinelearningmastery.com\/become-data-scientist\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Source<\/span><\/a><span style=\"font-weight: 400;\">.)<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Here\u2019s what you\u2019ll need to get the job:<\/span><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><span style=\"font-weight: 400;\">Master\u2019s or Ph.D. in computer science, engineering, mathematics, or statistics (although for many employers, experience can be a solid substitute)<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Experience working with Java, Python, and SQL<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Strong mathematical skills<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Strong analytical skills<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Experience in statistical and data mining techniques (like boosting, generalized linear models\/regression, random forests, trees, and social network analysis)<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Knowledge of advanced statistical methods and concepts<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Experience working with machine learning techniques such as artificial neural networks, clustering, and decision tree learning<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Experience using web services like DigitalOcean, Redshift, S3, and Spark <\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">5-7 years of experience building statistical models and manipulating data sets<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Experience analyzing data from third-party providers like AdWords, Coremetrics, Crimson, Facebook Insights, Google Analytics, Hexagon, and Site Catalyst<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Experience working with distributed data and computing tools like Hadoop, Hive, Gurobi, Map\/Reduce, MySQL, and Spark<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Experience visualizing and presenting data using Business Objects, D3, ggplot, and Periscope<\/span><\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Machine Learning Engineer vs. Data Scientist: Role Responsibilities<\/h2>\n\n\n\n<h4 class=\"wp-block-heading\"><span style=\"font-weight: 400;\">What Are the Responsibilities of a Machine Learning Engineer?<\/span><\/h4>\n\n\n\n<p><span style=\"font-weight: 400;\">The responsibilities of a machine learning engineer will be relative to the project they&#8217;re working on. However, if you explore the job postings, you\u2019ll notice that for the most part, machine learning engineers will be responsible for building algorithms that are based on statistical modeling procedures and maintaining scalable machine learning solutions in production.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Here\u2019s what these roles typically demand:<\/span><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><span style=\"font-weight: 400;\">Develop machine learning models<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Collaborate with data engineers to develop data and model pipelines<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Apply machine learning and data science techniques and design distributed systems<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Write production-level code<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Bring code to production<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Engage in code reviews<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Improve existing machine learning models <\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Be in charge of the entire lifecycle (research, design, experimentation, development. deployment, monitoring, and maintenance)<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Produce project outcomes and isolate issues<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Implement machine learning algorithms and libraries<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Communicate complex processes to business leaders<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Analyze large and complex data sets to derive valuable insights<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Research and implement best practices to enhance existing machine learning infrastructure<\/span><\/li>\n<\/ul>\n\n\n\n<p><span style=\"font-weight: 400;\">To get an idea of the variance of machine learning engineering jobs, we took a look at job postings on several different sites.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Here\u2019s a recent posting for a New York City-based machine learning engineer role at Twitter:<\/span><\/p>\n\n\n\n<figure class=\"wp-block-image\"><img loading=\"lazy\" decoding=\"async\" width=\"724\" height=\"936\" src=\"https:\/\/www.springboard.com\/blog\/wp-content\/uploads\/2019\/01\/image3.png\" alt=\"Twitter job posting\" class=\"wp-image-5769\" srcset=\"https:\/\/www.springboard.com\/blog\/wp-content\/uploads\/2019\/01\/image3.png 724w, https:\/\/www.springboard.com\/blog\/wp-content\/uploads\/2019\/01\/image3-400x517.png 400w, https:\/\/www.springboard.com\/blog\/wp-content\/uploads\/2019\/01\/image3-380x491.png 380w, https:\/\/www.springboard.com\/blog\/wp-content\/uploads\/2019\/01\/image3-700x905.png 700w, https:\/\/www.springboard.com\/blog\/wp-content\/uploads\/2019\/01\/image3-380x491.png 420w\" sizes=\"(max-width: 724px) 100vw, 724px\" \/><\/figure>\n\n\n\n<p><span style=\"font-weight: 400;\">(<\/span><a href=\"https:\/\/www.indeed.com\/viewjob?jk=8c5813cce48bb47f&amp;tk=1cvl8jve5ficq802&amp;from=serp&amp;vjs=3\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Source<\/span><\/a><span style=\"font-weight: 400;\">.)<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Here\u2019s a recent posting for a San Francisco-based machine learning engineer role at Adobe:<\/span><\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/www.springboard.com\/blog\/wp-content\/uploads\/2019\/01\/image2-1024x772.png\" alt=\"Adobe job posting\" class=\"wp-image-5770\"\/><\/figure>\n\n\n\n<p><span style=\"font-weight: 400;\">(<\/span><a href=\"https:\/\/www.indeed.com\/viewjob?jk=eab726f0e5c0adf1&amp;tk=1cvl9hetqficq80b&amp;from=serp&amp;vjs=3\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Source<\/span><\/a><span style=\"font-weight: 400;\">.)<\/span><\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><span style=\"font-weight: 400;\">What Are the Responsibilities of a Data Scientist?<\/span><\/h4>\n\n\n\n<p><span style=\"font-weight: 400;\">When compared to a statistician, a data scientist knows a lot more about programming. However, when compared to a software engineer, they know much more about statistics than coding.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Data scientists are well-equipped to store and clean large amounts of data, explore data sets to identify valuable insights, build predictive models, and run data science projects from end to end. More often than not, many data scientists once worked as <\/span><a href=\"https:\/\/www.springboard.com\/resources\/learning-paths\/data-analysis\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">data analysts<\/span><\/a><span style=\"font-weight: 400;\">.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Here\u2019s what the role typically demands:<\/span><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><span style=\"font-weight: 400;\">Research and develop statistical models for analysis<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Better understand company needs and devise possible solutions by collaborating with product management and engineering departments<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Communicate results and statistical concepts to key business leaders<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Use appropriate databases and project designs to optimize joint development efforts<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Develop custom data models and algorithms<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Build processes and tools to help monitor and analyze performance and data accuracy<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Use predictive modeling to enhance and optimize customer experiences, revenue generation, ad targeting, and more<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Develop company A\/B testing framework and test model quality<\/span><\/li>\n<\/ul>\n\n\n\n<p><span style=\"font-weight: 400;\">Here\u2019s a recent posting for a New York City-based data scientist role at Asana:<\/span><\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/www.springboard.com\/blog\/wp-content\/uploads\/2019\/01\/image5-1024x464.png\" alt=\"Asana job posting\" class=\"wp-image-5771\"\/><\/figure>\n\n\n\n<p><span style=\"font-weight: 400;\">(<\/span><a href=\"https:\/\/www.glassdoor.com\/job-listing\/data-scientist-asana-JV_IC1132348_KO0,14_KE15,20.htm?jl=2907798529&amp;ctt=1545974929507\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Source<\/span><\/a><span style=\"font-weight: 400;\">.)<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Here\u2019s another recent posting for a San Francisco-based data scientist role at Metromile:<\/span><\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/www.springboard.com\/blog\/wp-content\/uploads\/2019\/01\/image4-915x1024.png\" alt=\"Metromile job posting\" class=\"wp-image-5772\"\/><\/figure>\n\n\n\n<p><span style=\"font-weight: 400;\">(<\/span><a href=\"https:\/\/www.glassdoor.com\/job-listing\/data-scientist-metromile-JV_IC1147401_KO0,14_KE15,24.htm?jl=3005450351&amp;ctt=1545975151265\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Source<\/span><\/a><span style=\"font-weight: 400;\">.)<\/span><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Machine Learning Engineer vs. Data Scientist: Salary<\/h2>\n\n\n\n<h4 class=\"wp-block-heading\"><span style=\"font-weight: 400;\">How Much Does a Machine Learning Engineer Make?<\/span><\/h4>\n\n\n\n<p><span style=\"font-weight: 400;\">The wages commanded by machine learning engineers can vary depending on the type of role and where it\u2019s located. According to <\/span><a href=\"https:\/\/www.indeed.com\/salaries\/Machine-Learning-Engineer-Salaries\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Indeed<\/span><\/a><span style=\"font-weight: 400;\">, the average salary for a machine learning engineer is about $145,000 per year. <\/span><\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><span style=\"font-weight: 400;\">How Much Does a Data Scientist Make?<\/span><\/h4>\n\n\n\n<p><span style=\"font-weight: 400;\">What data scientists make annually also depends on the type of job and where it\u2019s located. Remember, it is a much broader role than machine learning engineer. That said, according to <\/span><a href=\"https:\/\/www.glassdoor.com\/List\/Best-Jobs-in-America-LST_KQ0,20.htm\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Glassdoor<\/span><\/a><span style=\"font-weight: 400;\">, a data scientist role with a median salary of $110,000 is now the hottest job in America. <\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">As the demand for data scientists and machine learning engineers grows, you can also expect these numbers to rise.<\/span><\/p>\n\n\n\n<p><em><strong>Related<\/strong>: <a href=\"https:\/\/www.springboard.com\/blog\/data-science\/machine-learning-engineer-salary-guide\/\" target=\"_blank\" data-type=\"URL\" data-id=\"https:\/\/www.springboard.com\/blog\/data-science\/machine-learning-engineer-salary-guide\/\" rel=\"noreferrer noopener\">Machine Learning Engineer Salary Guide<\/a><\/em><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Final Thoughts<\/h3>\n\n\n\n<p><span style=\"font-weight: 400;\">If you take a step back and look at both of these jobs, you\u2019ll see that it\u2019s not a question of <\/span><span style=\"font-weight: 400;\">machine learning vs. data science<\/span><span style=\"font-weight: 400;\">. Instead, it\u2019s all about what you\u2019re interested in working with and where you see yourself many years from now.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Let\u2019s summarize the questions posed at the beginning of this article:<\/span><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><span style=\"font-weight: 400;\">Data scientist vs. machine learning engineer<\/span><span style=\"font-weight: 400;\">: do they need a degree? <\/span>\n<ul class=\"wp-block-list\">\n<li><span style=\"font-weight: 400;\">Most employers would prefer an advanced degree, but to meet demand, they will be open to hiring those who have the right skills and experience.<\/span><\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Data scientist vs. machine learning engineer<\/span><span style=\"font-weight: 400;\">: what do they actually do? <\/span>\n<ul class=\"wp-block-list\">\n<li><span style=\"font-weight: 400;\">While there\u2019s some overlap, which is why some data scientists with software engineering backgrounds move into machine learning engineer roles, data scientists focus on analyzing data, providing business insights, and prototyping models, while machine learning engineers focus on coding and deploying complex, large-scale machine learning products.<\/span><\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Data scientist vs. machine learning engineer<\/span><span style=\"font-weight: 400;\">: who makes more? <\/span>\n<ul class=\"wp-block-list\">\n<li><span style=\"font-weight: 400;\">At present, machine learning engineers make more, but the data scientist role is a much broader one, so there is a wide variety of salaries depending on the specifics of the job.<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<p><span style=\"font-weight: 400;\">Whether you become a machine learning engineer or a data scientist, you\u2019re going to be working at the cutting edge of business and technology. And since <\/span><a href=\"https:\/\/www.monster.com\/career-advice\/article\/tech-talent-gap-survey-0816\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">the demand for top tech talent far outpaces supply<\/span><\/a><span style=\"font-weight: 400;\">, the competition for bright minds within this space will continue to be fierce for years to come. So you really can\u2019t go wrong no matter which path you choose. <\/span><\/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>There\u2019s some confusion surrounding the roles of machine learning engineer vs. data scientist, primarily because they are both relatively new. However, if you parse things out and examine the semantics, the distinctions become clear. At a high level, we&#8217;re talking about scientists and engineers. While a scientist needs to fully understand the, well, science behind [&hellip;]<\/p>\n","protected":false},"author":48,"featured_media":5773,"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-5767","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\/5767"}],"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\/48"}],"replies":[{"embeddable":true,"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/comments?post=5767"}],"version-history":[{"count":3,"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/posts\/5767\/revisions"}],"predecessor-version":[{"id":47623,"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/posts\/5767\/revisions\/47623"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/media\/5773"}],"wp:attachment":[{"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/media?parent=5767"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/categories?post=5767"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/tags?post=5767"},{"taxonomy":"marketing_tags","embeddable":true,"href":"https:\/\/www.springboard.com\/blog\/wp-json\/wp\/v2\/marketing_tags?post=5767"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}