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Is it worth switching from software developer to data scientist?

Last updated on: 
December 13, 2023
Utkarsh Sahu
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About The Author!
Utkarsh Sahu
Utkarsh Sahu
Director Category Management at Interview Kickstart. With a toolbox of P&L expertise, inventive innovations, marketing magic, and strategic relationships, he is an ambitious management consultant having a passion for promoting business growth.

Switching from one job role to another type comes with specific conditions. Transitioning from software engineering to data science varies per individual. The field of data science poses challenges on the basis of its multidisciplinary nature. One has to fulfill the requirements of knowledge and expertise. It is a tricky but not impossible transition, and above all, it is worth it. You just need to look into a few specifications to ensure the foundational shift, understanding the aspects of Data Science vs Software Engineering. Let’s look into what it takes to transition from a Software Developer to a Data Scientist position. 

Here is what we will cover:

  • Data Science and Software Engineering
  • Are Software Developers and Software Engineers the Same?
  • Data Scientist vs Software Developer
  • Software Developer to Data Scientist: Possibility of Transition
  • Factors Necessary For the Shift From Software Developer to Data Scientist
  • Similarities and Transferable Skills that Aid in the Transition
  • Build Your Potential in Data Science With Interview Kickstart
  • FAQs About Software Developer to Data Scientist

Data Science and Software Engineering

"Data science" is the statistical and analytical examination of huge datasets in order to create hypotheses and uncover patterns, which are frequently derived from complex program usage logs. It is more closely related to scientific and statistical subjects than to software engineering. Because of their significant statistical and analytical background, data scientists, including Ph.D. scientists and statisticians, frequently shift into this capacity smoothly. 

What do experts say?

“Data and data science greatly influence everything we do…The impact that data has and will have…continues to grow every day.”

–Ronald van Loon

(Recognised as a Top 3 Big Data Influencer by Onalytica)

They excel at activities like hypothesis generation, data analysis, charting, and data exploration, distinguishing it from software engineering. Software engineering is concerned with the design, development, and maintenance of software systems in a structured and methodical manner to assure reliability and quality.

Are Software Developers and Software Engineers the Same?

Both the terms Software Developer and Software Engineer are often used interchangeably. The main similarity between them is that both candidates are in software engineering and share many skills in common. Both professions are involved in coding, problem-solving, and contributing to software projects, with essential skills and expertise that are often the same among many businesses and sectors.

Software development entails generating and maintaining software applications, whereas software engineering entails planning, developing, testing, and upgrading software systems. A software engineer creates software architecture, builds codes, and assures the quality and stability of software.

Data Scientist vs Software Developer

Explore the differences to further learn about this career shift.

Criteria Software Developer Data Scientist
Technical Writing Technical documentation for software applications.
Communicates regarding code changes
Reports and documentation for data analysis (methodology, findings, & insights)
Communicates data-driven decisions to non-technical stakeholders.
Programming Languages Java, C++, Python, JavaScript, or C# Python and R
Database Management Familiar with database systems and SQL Experienced in working with databases and querying data
Professional Skills Skilled in all phases of the software development lifecycle (requirements gathering, design, development, testing, and deployment)
Problem-solving skills for algorithm development
Skilled with the data science project lifecycle (data collection, preprocessing, model building, evaluation, and deployment)
Problem-solving skills for identifying valuable insights
Version Control Proficient in using version control systems like Git Uses version control for managing code changes
Soft Skills Effective communication to understand project requirements
Task oriented
Effective communication for making data-driven decisions accessible
Curiosity-driven and analytical thinking
Domain Knowledge Expertise in specific industries for the development of some software applications
Not concerned with data context or potential biases.
Often requires domain-specific knowledge
Must be aware of data context, potential preferences, and ethical considerations
Statistical and Mathematical Proficiency Basic math skills and not advanced statistical knowledge A strong base of statistics and mathematics

Software Developer to Data Scientist: Possibility of Transition

To shift from software engineering to data science, acquiring key skills is essential:

  • Statistics, probability, and causality understanding
  • Strong Math proficiency
  • Hypothesis generation, data analysis, and visualization skills
  • Product thinking for successful strategies
  • Machine learning is beneficial but not always necessary

A few transition paths with different careers can go as follows:

  • Pursue a master's in statistics, machine learning, or predictive analytics
  • Work in data engineering to gain exposure and skills required for Data Science
  • Explore financial engineering for an experience similar to that of Data Science
  • Start with product management and learn statistics gradually to enrich your switch
  • Learn Statistics and Aim for Data Science Interview

Factors Necessary For the Shift From Software Developer to Data Scientist

Data Science has given us a unique viewpoint on how we view data. In today's data-driven marketplace, shifting from software development to data science brings mutual benefits. Your programming experience and skills in problem-solving are valuable perks. 

The key transition factors required for the career shift include the following:

  1. Clear Role Understanding: Decide your current and future roles.
  2. Data Scientist Responsibilities: Acquaint yourself with data scientist duties.
  3. Bridging Knowledge Gap: Address any skill gaps, particularly in statistics and data analysis.

With the proper planning and effort, this shift is attainable.

Key Transition Factors for Software Developer to Data Scientist Shift

Similarities and Transferable Skills that Aid in the Transition

Certain skills are common and transferable.

  1. Programming Skills: Strong programming skills are required by both software engineers and data scientists. Developers who are generally proficient in languages such as Python have an easier time transitioning.
  2. Problem-Solving Skills: Problem-solving is a shared skill. Developers work on software problems, whereas data scientists use it to draw insights from data.
  3. Data Handling: Software developers handle data in applications, gaining essential experience in data manipulation and data structure comprehension.
  4. Analytical Skills: Analytical thinking is also a shared skill. Data scientists gather insights while developers tackle problems rationally.
  5. Learning Skills: Software developers are used to constantly learning new technologies, so they adapt well to the constantly changing data science field.
  6. Mathematical Foundations: Software Developers usually have a mathematical base that can help to kickstart data science.
  7. Team Collaboration: Collaboration skills learned in software development transfer to interdisciplinary team situations in data research.
Similarities and Transferable Skills that Aid in the Transition to Data Science

Build Your Potential in Data Science With Interview Kickstart

Transitioning from software engineer to data scientist is a thrilling endeavor that demands careful planning and dedication. Knowing your potential allows you to focus on your key activities and abilities. If you're getting ready for a Data Science interview, browse the technical interview checklist, interview questions page, and pay negotiating e-book!

We have taught over 17,500 software engineers and understand what it takes to pass the most difficult technical interviews. Our graduates routinely receive job offers from FAANG+ organizations. The biggest offer ever received by an IK alum is $1.267 Million!

You will have the opportunity to study from experienced lecturers who are recruiting managers and tech leads at Google, Facebook, Apple, and other top Silicon Valley tech organizations at IK.

Want to nail your next tech interview? Sign up for our FREE Webinar.

FAQs About Software Developer to Data Scientist

1. Can a software engineer become a data scientist?

Both data scientists and software engineers master computer science basics, yet they apply their knowledge in diverse ways. Despite this, these two positions coincide in many ways, which is why professionals in software engineering frequently migrate to data science.

2. Is it possible to transition from software engineer to data scientist?

Yes, a Software Developer may transition to a Data Scientist's role by learning necessary skills such as statistics, machine learning, and data manipulation, as well as getting practical experience from personal projects and events.

3. How long does transitioning from a software developer to a data scientist take?

The transfer period depends on the individual's background and learning speed. Gaining the essential skills and expertise may take several months to a year.

4. Who earns more, Data Scientist or Software Developer?

Data Scientists' and Software Developers' earnings potential can vary depending on criteria such as experience, location, and industry. Due to their specialized skill set and diversified tasks, Data Scientists typically earn slightly higher incomes.

5. Is Software Engineering harder than Data Science?

Data Science can be harder or not harder depending upon the person’s knowledge, skills, and inclination. Both fields demand specific skill sets and academics for fulfilling the desired commitments of the job roles.

6. What are the average salary compensations for Software Developers vs Data Scientists?

The following salary estimates of Software Developers vs Data Scientists by Glassdoor show that a Data Scientist earns more than a Software Developer.

Job Title Average Salary AAdditional Cash Compensation Range
Software Developer $1,02,216/year $7,145 $5,359 - $10,003
Data Scientist $127,385/year $20,961 $15,721 - $29,346
Posted on 
December 11, 2023

Utkarsh Sahu

Director, Category Management @ Interview Kickstart || IIM Bangalore || NITW.

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