Job Summary: We are looking for a highly skilled Data Scientist with deep expertise in time series forecasting, particularly in demand forecasting and customer lifecycle analytics (CLV). The ideal candidate will be proficient in Python or PySpark, have hands-on experience with tools like Prophet and ARIMA, and be comfortable working in Databricks environments. Familiarity with classic ML models and optimization techniques is a plus. Key Responsibilities Develop, deploy, and maintain time series forecasting models (Prophet, ARIMA, etc.) for demand forecasting and customer behavior modeling. Design and implement Customer Lifetime Value (CLV) models to drive customer retention and engagement strategies. Process and analyze large datasets using PySpark or Python (Pandas). Partner with cross-functional teams to identify business needs and translate them into data science solutions. Leverage classic ML techniques (classification, regression) and boosting algorithms (e.g., XGBoost, LightGBM) to support broader analytics use cases. Use Databricks for collaborative development, data pipelines, and model orchestration. Apply optimization techniques where relevant to improve forecast accuracy and business decision-making. Present actionable insights and communicate model results effectively to technical and non-technical stakeholders. Required Qualifications Strong experience in Time Series Forecasting, with hands-on knowledge of Prophet, ARIMA, or equivalent Mandatory. Proven track record in Demand Forecasting Highly Preferred. Experience in modeling Customer Lifecycle Value (CLV) or similar customer analytics use cases Highly Preferred. Proficiency in Python (Pandas) or PySpark Mandatory. Experience with Databricks Mandatory. Solid foundation in statistics, predictive modeling, and machine learning
Locations: Mumbai/Pune/Noida/Bangalore/Jaipur/Hyderabad
Keyskills: Machine Learning Data Bricks Optimization Pricing Time Series Pyspark Arima Classic ML Artificial Intelligence Regression Customer Lifecycle Manufacturing Industry Regression Modeling Forecasting Data Science Xgboost Time Series Analysis Pandas Classical Python Prophet