From Fresher to Data Scientist: Yamini's Career Transformation

In the ever-evolving tech world, stories of reinvention and resilience stand out—and Yamini's journey from homemaker to data scientist is one such beacon of inspiration. After nearly nine years away from the workforce, Yamini chose to embrace change, stepping into the booming world of data science with no prior experience in software or coding.

Yamini opens up about her inspiring journey—how she overcame numerous challenges, transitioned from an electronics background into the tech world, and ultimately secured a Data Scientist position at Vistan Nextgen. Her story reflects not just a powerful career transformation, but also unwavering determination, continuous learning, and strong self-belief.

If you're from a non-technical background or have taken a long career break, watch DataMites success stories like Yamini’s to see how possible it is to break into data science—with the right mindset and support.

Yamini’s Inspiring Journey to Becoming a Data Scientist with DataMites

How did someone with no coding background and a 9-year career gap break into data science? In this Q&A, Yamini shares her path, challenges, and tips for aspiring professionals.

Q1: Can you tell us a bit about your background, Yamini?

I graduated in Electronics and Communication Engineering in 2016. Since then, I’ve been a full-time homemaker, managing my household and raising two kids. Recently, I decided it was time to reignite my career.

Q2: What motivated you to choose data science after such a long break?

My brother, who works in software, introduced me to data science. I was fascinated by how much data is used everywhere today. It felt like a powerful and growing field where I could find opportunities, even as a beginner.

Q3: Why did you choose DataMites for your training?

I liked that DataMites starts teaching from the very basics. Coming from a non-software background, this was essential for me. I was intimidated by coding at first, but their structured approach and step-by-step teaching style really helped.

Q4: How did you approach learning Python as a beginner?

I began with simple programs and gradually built up. Initially, I struggled with syntax and logic, but focusing on the basics helped. Once I understood the logic behind Python, I started enjoying it.

Q5: What was your biggest challenge during the course?

Confidence. I felt overwhelmed, especially after mock interview rejections. But I kept going. Consistency was key. Each failed attempt taught me what to improve.

Q6: How did DataMites support your interview preparation?

They conducted mock interviews—13 in total for me! Every mock helped me learn. They also provided datasets, project guidance, and resume templates that passed ATS filters. That played a big role in preparing me for real interviews.

Q7: What kinds of questions did you face in actual interviews?

In my final interview with Bon NextGen, I was given a dataset and asked to perform end-to-end analysis—cleaning, EDA, and solving a business problem. Previous interviews included Python and SQL MCQs and logic-based tasks.

Q8: Did you face machine learning-related questions?

Yes, in the final interview. They asked about ensemble techniques like bagging and boosting, and some basic questions on convolutional neural networks (CNNs).

Q9: How important was Python in clearing interviews?

Extremely important. Even if you don’t know advanced machine learning, strong Python skills can help you clear the initial rounds. Most technical tasks begin with coding.

Q10: What about statistics—were you asked any specific topics?

Yes. In every interview, I was asked about p-value—it’s a standard question. Other topics included skewness and kurtosis.

Q11: How did you address your career gap in your resume?

I was honest. I explained I was a homemaker due to family responsibilities. I also highlighted my recent training, projects, and skills. Transparency helped me gain trust.

Q12: What role were you offered, and what are your responsibilities?

I was offered an internship as a Data Scientist. The specific responsibilities are yet to be defined, but the focus seems to be on data wrangling and analysis.

Q13: Did you work on any projects during the course?

Yes, five capstone projects. I listed all of them in my resume with details like algorithms used and the accuracy achieved. Interviewers often asked questions based on those.

11. Were you asked machine learning or AI-related questions?

Yes, in one interview I was asked about ensemble methods (bagging, boosting) and basics of CNN (convolutional neural networks), especially since it was a robotics company.

Q14: How was your internship experience with Rubixe?

Wonderful! Even though I was part of the online batch, I felt deeply involved. I wasn’t in any formal group but managed independently. The practical exposure really helped.

Q15: What’s your message to others with career gaps or non-tech backgrounds?

Don’t give up. Learn consistently. Focus on basics—especially Python. Be honest in your resume. If I can do it after 9 years away, anyone can. Just stay consistent and believe in yourself.

Refer these articles:

• From Struggle to Success: Ajay Kumar’s Data Science Journey
• Mechanical Engineer to Data Scientist: Kariyappanavar’s Journey
• How Pratham Transitioned From ECE to a Data Science Role

Key Takeaways from Yamini’s Inspiring Journey into Data Science

When asked about her transition, Yamini shared practical insights that helped her move from a non-technical background into a data science role. Here's what stood out from her story.

• Yamini held a degree in Electronics and Communication but had no experience in coding or software development prior to starting her data science journey.
• After graduating in 2016, she spent nearly 9 years as a full-time homemaker before re-entering the workforce.
• Her brother, who works in software, introduced her to data science, sparking her interest in the field.
• Yamini selected DataMites because of their beginner-friendly, structured curriculum, which helped her overcome her initial fear of coding.
• She began with simple Python programs, gradually building logic and syntax understanding, which became a crucial foundation for her progress.
• The biggest challenge for her was self-doubt, especially after multiple failed mock interviews. Consistent effort helped her overcome this.
• Yamini completed 13 mock interviews through DataMites, which were crucial in preparing her for real job interviews.
• DataMites helped her build an ATS-friendly resume highlighting her capstone projects and skills, despite her long career break.
• Interviews included hands-on tasks like data cleaning and EDA, as well as questions on Python logic, SQL queries, and machine learning techniques.
• Topics like p-value, skewness, and kurtosis were frequently asked during interviews.
• She was asked about ensemble techniques (e.g., bagging, boosting) and CNN basics, especially by a robotics-focused company.
• Yamini was transparent about her time away from work due to family responsibilities, which interviewers appreciated.
• She completed an internship with Rubixe, gaining valuable hands-on experience in data analysis, even as a remote/online learner.
• She worked on five capstone projects, which she showcased in interviews—often leading to technical follow-up questions.
• After her preparation, Yamini landed a Data Scientist intern role, marking her successful transition into tech.
• Her key advice: focus on basics (especially Python), stay consistent, be honest about gaps, and believe in your potential.
• Yamini’s story exemplifies that a career break—even a long one—does not prevent you from entering high-demand fields like data science.

Yamini’s story is a testament to the power of resilience and lifelong learning. For anyone looking to make a career switch or re-enter the workforce after a break, her journey proves that it's never too late to learn, grow, and succeed.

With platforms like DataMites providing the right support, structured training, and real-world project experience, anyone—from homemakers to non-coders—can step into the world of data science with confidence.

Refer these articles:

• How to Become a Data Scientist in Kolkata?
• Data Science Course Fees in Kolkata
• Why Data Scientist Career in Kolkata

Today, data science is among the top IT courses in demand, unlocking exciting career opportunities for individuals from diverse educational and professional backgrounds. With data-driven decision-making becoming central to every industry, institutes like DataMites Institute are empowering thousands of learners, just like Yamini, to successfully transition into the rapidly evolving tech landscape.

If you're thinking of following in Yamini’s footsteps and stepping into the world of data science, now is the perfect time to upgrade your skills. According to Precedence Research, the global data science platform market was valued at USD 150.73 billion in 2024, is expected to reach USD 175.15 billion in 2025, and is projected to exceed USD 676.51 billion by 2034, growing at a CAGR of 16.20%. With the explosion of data across industries, the demand for skilled data professionals is on the rise. That’s why choosing a trusted training provider that offers hands-on projects, real-world exposure, and job assistance is key to launching a rewarding career. Enrolling in a top-rated data science institute in Kolkata, Bangalore, Chennai, Hyderabad, Pune, Mumbai, or Delhi can open doors to vast career opportunities.

For Yamini, who had a career gap of nearly nine years and came from a non-technical background in electronics, structured learning and expert mentorship were game changers. Through comprehensive programs in Data Science, Machine Learning, Python, and Data Analytics — backed by globally recognized certifications from IABAC and NASSCOM FutureSkills — she gained the confidence and technical know-how to break into the industry and secure a Data Scientist position at Vistan Nextgen.

DataMites Institute offers data science courses in Kolkata, Bangalore, Chennai, Hyderabad, Pune, Ahmedabad, Coimbatore, and Mumbai, along with flexible online learning options. This ensures high-quality, accessible education for fresh graduates, working professionals, and career switchers — just as it did for Yamini.