Mohit Maithani’s Journey as Data Analyst
Discover Mohit Maithani’s journey from CSE graduate to Data Analyst at Nestlé, driven by mentorship, hands-on learning, and advanced analytics. Learn how DataMites empowers aspiring professionals through expert-led training and global certifications.
Kriti Maurya
In today's data-driven world, transitioning from a CSE graduate to a Data Analyst role in a major MNC is no small feat. Mohit Maithani’s journey from academic projects to international assignments and complex NLP tasks at Nestlé illustrates the power of mentorship, hands-on learning, and continuous growth in forging a successful analytics career.
Mohit’s Data Analyst Journey from CSE Grad to Nestlé
Mohit Maithani, a Computer Science graduate, successfully transitioned into the role of a Data Analyst through focused learning and hands-on experience in top IT courses. From interning in computer vision projects to working with global companies, his journey is an inspiring blend of technical growth and practical application. Currently at Nestlé, Mohit shares valuable insights on breaking into the data analytics field.
Q: Could you share your background and career path?
Mohit: I graduated in Computer Science from Uttarakhand Technical University in 2020. During my studies, I completed Kaggle projects and joined DataMites in 2019, where Ashok Sir mentored me. Concurrently, I taught data science fundamentals at an ed-tech startup and co-founded a funded company.
Q: What happened after graduation?
Mohit: I did a data science internship focusing on fall detection via CCTV. Then, I worked with Analytics India Magazine, writing on AI and data science. Later, I joined a Dutch MNC as a Data Analyst & BI expert, working with dashboards, analytics, and traveling internationally.
Q: What is your current role at Nestlé?
Mohit: I’m a Data Analyst in the Learning & Talent Development team, managing South Asia’s regional database and deriving insights from learning metrics.
Q: What does a typical day look like for a Data Analyst?
Mohit: It varies by domain—sales, HR, supply chain. At Nestlé, I analyze employee data, derive insights, visualize trends, and occasionally build predictive models, such as NLP-based theme extraction from free-text employee feedback.
Q: How do Data Analyst and Data Scientist roles differ?
Mohit: Analysts focus on data manipulation, visualization, and descriptive analytics. Data Scientists integrate predictive modeling and machine learning. That said, the lines often blur—analytics roles can involve ML, as seen in my NLP project.
Q: Can analysts engage in advanced projects like NLP?
Mohit: Absolutely. I recently completed an NLP-based theme extraction module on employee feedback, handling long-form text inputs and extracting themes—a task often classified as data science.
Q: What does a typical Data Analyst do?
Mohit: Data Analysts work across domains—sales, HR, supply chain—cleaning data, deriving insights, visualizing results, and often supporting predictive modeling. Storytelling from data is the core of the role.
Q: How do Data Analyst and Data Scientist roles differ?
Mohit: Analysts focus on data cleaning, visualization, and interpretation; Predictive modeling and machine learning typically fall under the Data Scientist umbrella. However, modern Analyst roles increasingly incorporate ML and NLP.
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Q: What skills should aspiring Data Analysts focus on?
Mohit: Start with Python and Excel (advanced formulas/macros). Learn SQL, then pick a BI tool (Power BI or Tableau). Build small projects via Kaggle or GitHub. Focus on fundamentals and storytelling with data.
Q: How essential is coding for Analysts?
Mohit: Coding is crucial for handling large datasets—Excel works only for small data. For roles like HR analytics, Python and SQL are indispensable for cleaning, analysis, and automation.
Q: Is ChatGPT a threat to Data Analysts?
Mohit: No. ChatGPT is a tool—prompt engineering is emerging as a valuable skill. Like calculators, it enhances efficiency but doesn’t replace critical thinking and deep understanding. Adaptation is key.
Q: How important is portfolio and online presence?
Mohit: Extremely. I rarely applied directly—recruiters approached me due to my online portfolio, GitHub projects, and LinkedIn activity. A visible skill showcase matters more than luck.
Q: What traits do recruiters look for in Data Analyst candidates?
Mohit: Attitude—openness, teamwork, and learning mindset. Strong fundamentals in data handling. And most importantly, eagerness to learn new tools proactively, without waiting for assignments.
Key Findings from Mohit’s Inspiring Journey
Mohit Maithani’s inspiring transition into the world of data analytics offers valuable insights into how passion, continuous learning, and real-world application can shape a successful analytics career.
- Mentorship Fuels Growth: Guided mentorship, particularly from industry veterans like Ashok Sir, played a pivotal role in shaping Mohit’s foundational understanding and career direction.
- Hands-on Projects Shape Careers: Real-world experience—through Kaggle competitions, internships in computer vision, and NLP initiatives—helped Mohit bridge the gap between theory and application.
- Teaching Reinforces Learning: Co-founding an ed-tech startup and teaching data science fundamentals solidified his knowledge while enhancing communication and leadership skills.
- Corporate Roles Offer Broad Exposure: Mohit’s journey includes working across varied domains such as finance, manufacturing, HR, and learning analytics—proving that data analytics is relevant in every business vertical.
- Analyst Roles Can Scale in Complexity: Data Analyst positions aren’t confined to basic analysis—Mohit’s role involved advanced automation and natural language processing, reflecting the evolving nature of the profession.
- Data Skills Unlock Global Opportunities: His analytics expertise led to international exposure, including projects and exhibitions across countries like Germany and the UAE, showcasing the global demand for skilled data professionals.
- Job Titles Are Becoming Interchangeable: The line between Data Analyst and Data Scientist is increasingly blurred, with responsibilities overlapping in areas such as machine learning, AI, and advanced analytics.
Mohit Maithani’s trajectory—from student to global Data Analyst—highlights how mentorship, real-world projects, and continuous learning can elevate one’s career. His story is a roadmap for aspiring analytics professionals aiming to make a meaningful impact in the industry. The Mordor Intelligence report depicts, the data analytics market is projected to reach USD 187.57 billion by 2026, growing at a CAGR of 25.4%.
Refer to the articles below:
- How to Become a Data Analyst in India
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Enrolling in a Data Analyst course in Dehradun or other leading tech cities like Pune, Chennai, Coimbatore, Hyderabad, Ahmedabad, Delhi, Chandigarh, Jaipur, and Mumbai opens doors to immersive industry exposure, valuable networking, and promising career opportunities in data analytics and software development.
DataMites Institute stands as a top-tier training provider, offering expert-led programs in Data Science, Artificial Intelligence, Machine Learning, Python Programming, Data Analytics course with internship, Data Engineering, and IoT. With hands-on training through live projects and internships, we equip learners with practical skills and strong placement support. Become a part of our thriving alumni network and take a confident leap in your data career with DataMites!
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