The Automotive Practice at Epsilon is seeking a Data Scientist II to deliver end-to-end data science projects supporting automotive clients. Responsibilities include data analysis, feature engineering, predictive modeling using AI/ML/DL techniques, model validation, automation, ETL processes, and presenting insights. Candidates should have 2-4 years of data science experience, strong coding skills in Python, PySpark, SQL, and knowledge of ML/DL algorithms. Familiarity with LLM, Generative AI, Databricks, AWS or Azure, and large data set handling is required. Automotive business and digital marketing knowledge preferred. Strong communication, problem-solving skills, and ability to work independently are essential. Location: Bengaluru, Karnataka, India.
What you'll do
Deliver end to end Data Science projects including understanding business requirements, exploratory data analysis, data processing, feature engineering, building and validating predictive models, explaining model results and insights
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Requirements
Master’s or Bachelor’s Degree in quantitative field (Statistics, Economics, Mathematics, Data Science, Business Analytics)
2-4 years of experience as a Data Scientist deploying Data Science projects
2+ years of coding skills in Python, PySpark, and SQL
Deep understanding and hands-on experience with ML and DL Algorithms
Good understanding of LLM, Gen AI, Databricks and Cloud Systems (AWS or Azure)
Experience working with large data sets and developing scalable solutions
Knowledge of Automotive Business and Digital Marketing Campaigns preferred
Ability to work independently and deal with ambiguity
Strong analytical and problem-solving skills
Excellent presentation and communication skills
Strong written and verbal communication skills
Highly motivated and collaborative team player with strong interpersonal skills
Employee well-being focusCollaborative work environmentOpportunities for growth through learning, development and career advancementInnovation-driven cultureWork-life balance and flexibilityDiversity and inclusion commitment
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