Industry Spotlight Session on Career in Data Science

Industry Spotlight Session on Career in Data Science. The Department of Statistics and Data Science, CHRIST (Deemed to be University), Pune Lavasa Campus, organised an Industry Spotlight Session on “Career in Data Science” on 29 August 2026. The session was conducted by Mr Amit Jain, an experienced data science and technology professional with academic training in Data Science, Business Analytics, Big Data and Information Technology. He has been associated with organisations such as Cybage, Wipro, Cloudmantra, Open Insights, TorcAI Digital Media and Findability Sciences. The session was designed to introduce students to the field of Data Science and help them understand the range of career opportunities available within the data and artificial intelligence ecosystem. It began by highlighting how everyday digital activities—including online searches, purchases, location services, messages, images and interactions with mobile applications—continuously generate large volumes of data. Students were introduced to the importance of transforming raw data into meaningful information, useful insights and appropriate actions. Mr Amit Jain explained that Data Science combines business

understanding, statistics, programming, data management and modelling to identify patterns and support effective decision-making. He presented the typical workflow of a data science project, beginning with defining the right problem and collecting relevant data. This is followed by cleaning and validating the data, applying statistical or machine-learning models, communicating the findings and using the results to recommend or automate appropriate actions. The session emphasised that the primary responsibility of a data scientist is to solve meaningful problems rather than merely build complex models. The participants were also introduced to descriptive, predictive and prescriptive analytics. Descriptive analytics helps organisations understand what has already happened, predictive analytics estimates what is likely to happen, and prescriptive analytics recommends suitable actions. Practical applications such as house-price prediction, customer-churn analysis, recommendation systems, fraud detection, customer segmentation, sentiment analysis, sports analytics, chatbots and targeted advertising helped students understand how these approaches are applied in different sectors. The session provided an overview of the wide use of Data Science across retail, e-commerce, healthcare, banking, insurance, education, agriculture, telecommunications, logistics, digital marketing and government services. Industry

examples were used to demonstrate how organisations analyse customer behaviour, provide personalised recommendations, predict demand, plan promotions, improve inventory management and support business decisions. Students were reminded that domain knowledge is as important as technical expertise when solving real-world problems. A major focus of the session was the variety of career pathways available in the field. Roles such as Data Analyst, Business Analyst, Business Intelligence Analyst, Data Engineer, Data Scientist, Machine Learning Engineer, Artificial Intelligence Engineer, Generative AI Engineer and Decision Scientist were discussed. Mr Amit Jain explained that students could choose a career direction based on their interests in business, technology, statistics, mathematical modelling or communication. The session also presented a beginner-friendly learning roadmap. Students were encouraged to develop foundations in mathematics, statistics, Python or R, SQL, data visualisation and exploratory data analysis before moving towards machine learning, deep learning, natural language processing and Generative AI. Equal importance was given to problem framing, communication, data quality, ethics and the responsible use of artificial intelligence. Mr Amit Jain advised students to build practical projects rather than depend solely on certificates. He encouraged them to create well-documented portfolios through platforms such as GitHub and LinkedIn and to demonstrate how they could solve real problems using data. Students were also guided to present each project clearly by explaining the problem, dataset, approach, results, limitations and practical value. The Industry Spotlight Session gave students a clear and realistic introduction to Data Science and its career possibilities. It helped them understand the skills expected by the industry and the steps required to move from learning to internships and employment. The session concluded with a practical message for students: begin with strong foundations, work consistently, complete meaningful projects, communicate results clearly and continue improving through feedback and experience.