Data Scientist vs. Software Developer – Profiles, Skills, and Job Responsibilities

Data-driven methodologies, as well as innovative software products and applications, have revolutionized today’s digital era. How many times have you heard how data science and software development are the skills of the future? There has been an astonishing increase in investments in data science and software development by organizations globally. These two job profiles may intersect at one point, considering some of the common skill sets required for both data scientists and software developers to possess. The article discusses data science and software development in detail by focusing on the key differences in data scientist vs. software developer careers.

Software developers have a wide scope of expertise in programming and coding. They are responsible to develop scalable applications, features, and functionalities for the end-users, while data scientists work towards collecting, analyzing, and processing huge volumes of data for business usage. Data scientists have wider skill sets, including knowledge of computer science, coding, programming, math, statistics, machine learning algorithms, deep learning, and programming languages like Python, R, etc.

To learn more about data science, read our blog – What is data science?

In this article, we will talk about the profile, roles, and skills required for both a data scientist and software developer profiles and the major differences in their roles. Let’s start with data scientists.

Data Scientist

Data Science is among the most talked about and highly paying domains of the technology industry in the past few years Harvard Business Review had gone one step ahead in 2012 and called ‘data scientist’ one of “the sexiest jobs in the 21st century.” Looking ahead at the future of data science, one can applaud the foresight of that tagline. Data science is a multidisciplinary field where a blend of data inference, algorithm development, and technology is used to solve analytical problems or provide insights into data. Data scientists need to have a working knowledge of mathematics, computer science, digital tools and technologies, statistics, artificial intelligence, or machine learning.

Must Explore – Data Science Courses

Job Responsibilities of a Data Scientist

Some common job responsibilities of a data scientist are –

• Data collection from different sources
• Data structuring using programming tools
• Create project blueprints or models
• Use machine learning algorithms and tools for computation
• Build analytics systems
• Perform exploratory data analysis
• Implement and predict your final model in the business ecosystem
• Present data through data visualizations through data dashboards, graphs, and other mediums for stakeholders (e.g. MS Excel, Seaborn, Tableau, etc.)

Read More – How to become a data scientist?

What Skills are Required to Become a Data Scientist?

Technical Skills

To succeed as a data scientist, you should have a command over –

• SQL and NoSQL databases
• Relational algebra
• Parallel databases
• Parallel query processing
• Scala
• Java
• SQL (Structured Query Language)
• Data Visualization
• Machine learning
• Statistical modeling
• Experimental design
• Bayesian inference
• Decision trees
• Python libraries
• Data optimization
• Storytelling
• High-quality visual representation
• R packages domain like ggplot2
• Ability to modulate the data into actionable decisions
• Graphical display tools

Must Read – Statistical Methods Every Data Scientist Should Know

Business Skills

• Great organizational and leadership skills
• Excellent communication skills
• Business Mindset

Software Developer

A software developer is responsible for analyzing the client’s specifications and requirements, and designing and testing the final software product. They create, test, and implement functional software products and applications. Software developers also evaluate existing operations, find bugs, if any, and fix them. Software developers are also responsible for improving existing software development processes and proposing improved ones.

A software developer’s main job responsibilities include the following –

• Prepare and install software solutions as per client specifications
• Maintain and improve existing codebases
• Develop, test, and implement software systems
• Manage software development lifecycle
• Examine any issues in the development lifecycle
• Analyze, debug, and test the software
• Find and troubleshoot production and non-production applications
• Write efficient, verifiable, and reliable codes
• Read and analyze research reports and customer suggestions.
• Prepare and publish software updates
• Evaluate complex data models

What Skills are Required to Become a Software Developer?

A software developer must possess the following skillsets:

Technical Skills

• Knowledge of computer programming languages
• Ability to provide workable solutions
• Analytical and reasoning skills
• Proficiency in troubleshooting software issues
• Strong programming and modeling skills
• Software design, documentation, and testing skills
• Backend development skills

Must Read – 10 Best Software Development Tools and Frameworks to Learn

Business Skills

• Logical thinking
• Time-management
• Good communication
• Attention to detail
• Sense of ownership
• Critical thinking

Data Scientist vs. Software Developer

We now move on to the major difference between data scientist vs. software developer. Here they are –

Data Scientist	Software Developer
Involves data collection, analysis, and processing	Involves applications and features development
Includes machine learning and statistics	Focuses more on coding languages
Data scientists work with machine learning algorithms, data visualization and analytics tools, and databases.	Software developers work with programming, database services, plan instruments, software development, integration processes, etc.
Focused on management and business decision making	Focuses on systems building
Process-oriented	Based on the methodology of the software development cycle
Skills – Knowledge of Programming, Statistics, Math, and Artificial Intelligence. Machine learning, Data Mining, etc.	Skills – Ability to program in multiple languages, Knowledge of coding, Software Design & Documentation, etc.

Conclusion

I hope you get some clarity over data scientist vs. software developer! Both profiles are crucial to any business. There is personal aspiration and interest in what you want to become. Both profiles require different skills, knowledge of tools, and languages; however, they also share some qualities of those same aspects. If you like to create new things and know you are interested in set outcomes, software development is for you. On the other hand, if you love getting your hands dirty with lots and lots of data, making predictions basis your findings, and having the flair for digging deep into statistics and trends, data science is for you. Take your pick and make the right decision!

_______________

If you have recently completed a professional course/certification, click here to submit a review.