Data Scientist Mumbai (India)

Key Responsibilities Data Analysis & Insights: Analyze large datasets from multiple sources (clickstream, sales, user engagement) to uncover insights and support business decision-making. Machine Learning: Develop, deploy, and maintain machine learning models for recommendations, personalization, customer segmentation, demand forecasting, and pricing. A/B Testing: Design and analyze A/B tests to evaluate the performance of product features, marketing campaigns, and user experiences. Data Pipeline Development: Work closely with data engineering teams to ensure the availability of accurate and timely data for analysis. Collaborate with Cross-functional Teams: Partner with product, marketing, and engineering teams to deliver actionable insights and improve platform performance. Data Visualization: Build dashboards and visualizations to communicate findings to stakeholders in an understandable and impactful way. Exploratory Analysis: Identify trends, patterns, and outliers to help guide business strategy and performance improvements. Required Skills: Proficiency in Python or R: Experience in using Python or R for data analysis and machine learning. SQL: Robust SQL skills to query and manipulate large datasets. Machine Learning Frameworks: Familiarity with libraries such as Scikit-learn, TensorFlow, or PyTorch. Data Wrangling: Ability to clean, organize, and manipulate data from various sources. A/B Testing: Experience designing experiments and interpreting test results. Visualization Tools: Proficiency with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn). Statistics & Probability: Strong grasp of statistical methods, hypothesis testing, and probability theory. Communication: Ability to convey complex findings in explicit, straightforward terms for non-technical stakeholders. Preferred Qualifications: E-commerce Experience: Experience working with e-commerce datasets (e.g., user behavior, transaction data, inventory, and prod .