Partha’s Data Science Journey: From Beginner to Data Scientist

The field of data science is growing rapidly, offering numerous opportunities for individuals from various backgrounds. However, transitioning into this field requires structured learning, hands-on experience, and strong interview preparation.

To help aspiring data scientists, we interviewed Partha, a software developer who successfully switched careers and landed a job as a Data Scientist at Sirpi Products after completing the DataMites Data Science Program.

If you're an aspiring data scientist, this blog will give you valuable real-world insights on landing your first data science job.

Partha’s Data Science Journey and Background with DataMites

Partha transitioned from a software development background to data science, driven by his passion for analytics and machine learning.

Q1. What was your background before switching to data science?

I have completed my B.Tech in Electronics and Communication Engineering from West Bengal. My technical background helped me build a strong foundation, but I wanted to shift toward data science because of my interest in analytics and machine learning. I worked with SQL and programming in my previous role, which helped me during my transition. However, I had to learn machine learning, statistics, and deep learning from scratch.

Q2. Why did you choose data science as your career?

I was always interested in data-driven decision-making and problem-solving. Data science is an exciting field with great career growth, so I decided to upskill and switch my domain.

Q3. How did DataMites help you transition into data science?

The DataMites Data Science program provided structured training on:

• Python programming (essential for data science)
• SQL for database management
• Machine Learning & Deep Learning
• Statistics & Data Analytics

The learning management system (LMS) was really helpful, and I also got access to mock interviews and job placement support.

Q4. How long did it take for you to land a job?

After completing my training, I spent about three weeks preparing for interviews. Then, I applied for jobs through DataMites' Placement Assistance Team (PAT).

I secured my first data science job about two and a half months after completing my internship.

Q5. Can you tell us about your current role and responsibilities?

I am currently working as a Data Scientist at Sirpi Products. My responsibilities include:

• Analyzing large datasets to extract valuable insights
• Developing machine learning models to solve business problems
• Optimizing data pipelines and ensuring data quality
• Collaborating with different teams to support strategic decision-making

The role is dynamic and requires a problem-solving mindset, which I really enjoy.

Q6. What type of companies did you apply to?

I applied to multiple companies through DataMites’ PAT Team. They provided curated job listings based on my skills. I didn’t apply on external job portals—my entire hiring process was through DataMites.

Q7. Was the interview process online or in-person?

Since I was not in Bangalore at that time, my interviews were conducted online.

Q8. How many interview rounds were there?

My interview process had three rounds:

• Two technical rounds (Python, SQL, ML concepts)
• One HR round (soft skills, salary discussion, etc.)

Q9. What were the key topics discussed in the interview?

The technical rounds focused on:

• Python: Lists, dictionaries, tuples, lambda functions, OOP concepts
• SQL: Joins, queries, window functions
• Machine Learning: Regression vs classification, key ML algorithms
• Statistics: Hypothesis testing and statistical significance

Q10. Did they ask you to code in the interview?

Yes, I had to share my screen and write code live. The interviewer asked me to solve Python problems related to:

• Data structures (lists, dictionaries)
• Functions and Lambda functions
• Basic SQL queries

They also asked me to explain my code step by step.

Q11. Were there questions on machine learning?

Yes, they asked:

• What is regression vs classification?
• How do you determine which model to use for a dataset?
• What are the key differences between supervised and unsupervised learning?

Since I had listed machine learning projects on my resume, they also asked me to explain the concepts behind my projects.

Q12. Were there any deep learning questions?

Yes, they asked about CNN (Convolutional Neural Networks), but when I mentioned I wasn’t familiar with it, they said it was fine.

Deep learning is not mandatory for most entry-level data science jobs.

Q13. What is the average salary for freshers in data science?

For freshers, the starting salary is typically:

• ₹4-5 LPA in India
• Higher for those with prior IT experience

Q14. Are you working in an office or remotely?

I work onsite in Bangalore. My job is not remote or hybrid.

Q15. Are you working in a team or individually?

I work in a team of data scientists. Collaboration is an important part of the job.

Q16. Was the DataMites Python training enough to crack the interview?

Yes! The DataMites Python syllabus was sufficient, but I also practiced on:

• YouTube tutorials
• Medium blogs on Python and ML concepts

Q17. Did you apply for jobs outside DataMites' placement assistance?

No, all my job applications were through DataMites’ PAT Team.

Q18. What’s your advice for freshers preparing for data science interviews?

• Master Python & SQL: Focus on data structures, functions, and queries.
• Understand Machine Learning Basics: Know when to use regression vs classification.
• Practice Live Coding: Be ready to write and explain code in interviews.
• Improve Communication Skills: All interviews are in English, so practice speaking clearly.
• Keep Learning: Use YouTube, blogs, and practice problems to deepen your understanding.
• Be Patient: The job search takes time, so keep applying and improving.

Refer these articles:

• From BPO to Data Scientist: Babul Kumar’s Inspirational Journey
• From Passion to Profession: Sweta Rai’s Inspiring Data Science Journey
• First Steps in Data Science: Shreenidhi’s Journey to Success

Essential Career Insights from Partha’s Data Science Journey

Discover key takeaways from Partha’s transition into data science, including interview strategies, learning resources, and industry expectations.

• Career Transition from Software Development to Data Science – Prior experience in SQL and programming helped Partha transition smoothly into data science.
• Comprehensive Learning Approach – DataMites' LMS content was sufficient, but additional learning from YouTube and Medium blogs was beneficial.
• Importance of Python & SQL – Interviews focused heavily on Python data structures (lists, dictionaries, tuples) and SQL queries (window functions, joins, and subqueries).
• Real-World Projects Are Crucial – Hands-on experience in machine learning and deep learning projects played a key role in interview selection.
• Mock Interviews & Job Readiness – Participating in mock interviews helped improve confidence and boost interview performance.
• Data Science Interview Process – Coding rounds included writing and explaining Python scripts, working with data structures, and machine learning concepts.
• Technical Interview Focus – Covered machine learning algorithms, statistics-based tests, and ML model selection criteria.
• Role of Placement Assistance – Applied to jobs only through DataMites’ Placement Assistance Team (PAT) and secured a role in 2.5 months.
• First Data Science Job – Joined Sirpi Products as a Data Scientist, working on ML model development and data analysis.
• Team Collaboration – Works in a team setting rather than individually, emphasizing collaboration in projects.
• Deep Learning Knowledge Not Mandatory – While deep learning questions were asked, lack of experience in CNN was not a dealbreaker.
• Freshers’ Salary Expectations – Data Science salaries for freshers range between ₹4–5 LPA, with growth potential based on performance.
• Soft Skills & Communication Matter – Interviews were conducted entirely in English, and good communication skills were essential.

Partha’s journey from a software developer to a data scientist highlights the importance of structured learning, real-world projects, and persistent effort. His story is a testament to the fact that anyone with dedication and the right resources can break into the data science field.

Refer these articles:

• Why Data Scientist Career in Pune
• Why Data Scientist Career in Bangalore
• Why Data Scientist Career in Chennai

If you’re aiming for a successful career in data science, enrolling in top data science courses in Hyderabad, Bangalore, Pune, Chennai, Mumbai, Delhi, Ahmedabad, Coimbatore, and other metro cities in India can give you a competitive edge. According to a MarketsandMarkets report, the data science industry is projected to reach USD 322.9 billion by 2026, with a CAGR of 27.7%. To stay ahead in this evolving field, choose an institute that provides hands-on projects, internships, and strong placement support to boost your career prospects.

DataMites institute is a premier institute specializing in Data Science, Artificial Intelligence, Machine Learning, Python Development, and Data Analytics. With accreditation from IABAC and NASSCOM FutureSkills, it provides high-quality, industry-relevant training led by experienced professionals.

The institute focuses on practical learning through real-world projects, internship programs, and dedicated placement assistance, ensuring students gain valuable experience and keep up with industry trends. DataMites offers a data science offline  institute in Bangalore, Hyderabad, Chennai, Pune, Ahmedabad, Coimbatore, and Mumbai, catering to learners across India.

With expert mentorship, a structured curriculum, and a strong placement record, DataMites equips aspiring data scientists with the necessary skills to thrive in the industry. Whether you're a fresh graduate, working professional, or career switcher, DataMites provides a well-defined path to success in Data Science, AI, and Machine Learning.