Data Scientist (Senior)

Location: Gurugram Experience: 5–7 Years Company: Blu. Pine Energy Pvt. Ltd. Role Objective To develop and deploy data-driven tools and analytical models that improve renewable energy generation forecasting, Firm and Dispatchable Renewable Energy (FDRE) project performance, dispatch decisions, and power market operations across Blu.

Pine’s portfolio. The role will focus on leveraging data science, machine learning, time-series forecasting, and optimisation techniques to support efficient scheduling, reduce deviation settlement mechanism (DSM) exposure, and enhance operational and commercial decision-making.

Key Responsibilities

Develop generation forecasting models for solar, wind, and Battery Energy Storage System (BESS)-backed FDRE projects using weather forecasts, plant data, and historical performance. DSM and FDRE Performance Analytics: Build analytical tools to monitor and improve DSM and FDRE project performance, including deviation analysis, dispatch against Power Purchase Agreement (PPA) obligations, BESS utilisation, and identification of corrective actions.

Day-Ahead and Intraday Scheduling: Develop forecasting and analytical models to support day-ahead and intraday scheduling decisions and minimise DSM exposure. Optimisation Modelling: Build optimisation models for BESS charging and discharging, FDRE dispatch, and merchant market sales, considering PPA obligations, technical constraints, and power market prices.

Decision-Support Tools: Develop automated scheduling systems and decision-support tools that provide actionable recommendations to trading and operations teams. Data Integration and Dashboards: Integrate SCADA, weather, scheduling, and power market data into reliable analytical datasets, automated data pipelines, and dashboards.

Model Monitoring and Improvement: Monitor model performance, investigate forecasting errors, identify performance gaps, and continuously improve analytical tools as new operational data becomes available. Cross-Functional Collaboration: Work closely with Energy Markets, O&M, trading, and technology teams to deploy analytical models and tools for regular operational use.

Candidate Profile Strong hands-on experience in Python, SQL, time-series forecasting, machine learning, and optimisation techniques. Proven experience in developing and deploying data pipelines, analytical models, or decision-support applications. Preference for candidates from renewable energy companies with direct exposure to solar, wind, BESS, or FDRE operations.

Understanding of renewable energy forecasting, scheduling, DSM, SCADA data, or Indian power markets will be an added advantage. Ability to independently own technical projects, solve complex analytical problems, and translate model outputs into actionable business recommendations. Strong analytical, problem-solving, and communication skills, with the ability to explain technical recommendations clearly to commercial and operations teams.

Measures of Success Improved solar and wind generation forecasting accuracy. Reduced DSM exposure through improved forecasting, analysis, and scheduling decisions. Enhanced visibility and operational performance of FDRE dispatch and BESS utilisation. Development and regular adoption of reliable analytical tools by operating teams.

Reduced manual intervention through automation of scheduling, monitoring, and decision-support processes.