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Data Scientist | Automotive Domain | ML & Marketing Analytics

5 years

0 Lacs

Posted:3 weeks ago| Platform: Linkedin logo

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Job Description

About Company: Hansa Cequity is one of the leading data-driven, connected CX services providers in India. We offer integrated solutions in Marketing, Data Analytics, MarTech, Campaign Management, Digital, and Contact Center services to help clients acquire, engage, and retain customers profitably. By combining data-driven marketing strategy with cutting-edge technology, we empower brands to understand their customers deeply and build meaningful, multichannel engagement. Our goal is to deliver measurable business growth using best-in-class tools, platforms, and insights. We are recognized among the Top 50 Analytics Companies in India . To learn more, visit: www.hansacequity.com LinkedIn: Hansa Cequity Job Description: We are seeking a Data Scientist with strong expertise in classical machine learning and experience working with automotive datasets . The role focuses on building predictive models, marketing mix analysis, and end-to-end data pipeline development. Experience in marketing analytics is essential. Exposure to Generative AI is a plus, not a requirement. Key Responsibilities: Develop and deploy ML models (classification, regression, forecasting) for business use cases in the automotive domain. Analyze customer and vehicle data to derive insights for campaigns, retention, and personalization. Implement NLP techniques and marketing mix models for campaign optimization. Build data pipelines to ensure clean and real-time data processing. Collaborate with cross-functional teams to translate insights into strategy. Qualifications: Bachelor’s/Master’s in Computer Science, Data Science, or related field. 3–5 years of experience in ML and marketing analytics. Strong in Python, R, SQL, Azure; experience with scikit-learn, XGBoost, TensorFlow, or PyTorch. Automotive domain experience is mandatory. Familiarity with GenAI tools (OpenAI, LangChain, etc.) is a bonus or a plus point. Show more Show less

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