By 2025, the World Economic Forum estimates that 463 exabytes of data will be generated every day. For context, that would mean 300 billion movies of 1.5 GB each — and as of now, IMDB has only a little over 1.5 million titles. All this data would require skilled professionals to manage and make sense of — some would be data scientists, some other machine learning engineers. Oh wait, what’s the difference, you ask? Well, there’s plenty. And in this blog post addressing — machine learning engineer vs data scientist — let’s look at them all. 

We will demystify these two careers across jobs they do, skills they need, salaries they’ll earn and their growth path. 

Machine Learning Engineer vs Data Scientist: What is the Difference?

Think of it as the difference between scientists and engineers. Scientists create a body of knowledge based on the physical and the natural world, whereas engineers apply that knowledge to build, design and maintain products or processes.

A similar parallel can be made of ML engineers and data scientists as well. A data scientist collects, processes and makes meaning out of data. With the data scientist’s results, a machine learning engineer builds models that can help systems learn to record and interpret data on their own. They also take these models and deploy them to production for large-scale use.

Data Scientist Careers: What Does A Data Scientist Do?

This data scientist job description for a position at BookMyShow gives an idea of what a standard data scientist role would entail.

Machine Learning Engineer vs Data Scientist: Data Scientist Job Description
Source: LinkedIn

On a typical day, data scientists combine mathematics, statistics, programming and domain expertise to draw business insights and conduct predictive forecasting from structured and unstructured datasets. 

Take the story of how Indian Oil Corporation Limited (IOCL), a public sector undertaking, uses data science for business intelligence. IOCL is one of the two suppliers for household LPG in India. Prior to integrating all their data, they would get to know about a subsidised LPG cylinder being diverted only post-facto. 

Now, their centralised information system gives real-time information, alerting them ahead of any diversions. This way, customers who are paying for their gas cylinders get them on time without losing anything to pilferage, a common problem in the past. Data scientists enable such business interventions.

Data Scientist Skills

Machine Learning Engineer vs Data Scientist

Depending on the kind of data science role you’re taking up, you might need a combination of various skills. However, in general, the following are expected:

  • Statistical skills — statistical inference, databases, data wrangling etc.
  • Programming languages — Python, R, SAS, SQL
  • Data visualisation — Tableau, PowerBI, D3.js
  • Big data platforms — Oracle, Cloudera
  • Machine learning — Natural language processing, classification, clustering

Data Scientist Jobs

There are many career paths available to a data scientist. While ‘data scientist’ is a standard title, many other professionals such as BI developer, data engineer, data architect also perform key data science functions.

Data Scientist Salary

Data scientists earn an average of Rs 9,00,000 a year, and their salaries can go up to Rs 20,00,000 a year.

Source: LinkedIn

Machine Learning Careers: What Does a Machine Learning Engineer Do?

Machine learning engineers teach machines to mimic behaviours of humans. This could be Siri or Cortana that understands spoken orders from people; or fraud detection mechanisms that flag anomalies in your credit card usage; or the computer vision technology that helps identify cancerous cells in patients.

A machine learning engineer’s role is to create systems that can use data — from a data scientist’s work — and build models that think intelligently. This machine learning engineer job description at automation major UiPath gives a clear picture of what ML engineers do.

Source: LinkedIn

Machine Learning Skills

An ML engineer needs to be as strong in statistics and mathematics as data scientists need to be. The foundation is key. In addition, they also need skills in:

  • Programming with Python; knowledge of Keras, PyTorch etc.
  • Data wrangling and APIs
  • Supervised and unsupervised algorithms
  • Statistics for AI
  • Natural Language Processing
  • Deep learning and computer vision

Machine Learning Engineer Jobs

In addition to a machine learning engineer role, those with ML skills can also find jobs as AI developers, AI/ML researchers, decision scientists and so on. 

Machine Learning Engineer Salary

According to Glassdoor, machine learning engineer salary is Rs 11,00,000 a year, on an average.

Source: Glassdoor

So, Who Wins: Machine Learning Engineer vs Data Scientist?

If you’re looking to choose a career, it’s not a contest between machine learning engineer and data scientist at all. Each role performs a specific job, and the opportunities are endless. The growth in data across the world opens up opportunities for data scientists. The need for automation and possibilities for predictions makes ML engineers valuable. Many of the skills and experiences are also interchangeable. 

Start your career in data science with Springboard’s Data Science Career Track. In addition to a job-ready curriculum, hands-on portfolio projects, 1:1 mentorship, and career coaching, it also offers a job guarantee.