Lead Data Scientist

We are seeking a Lead Data Scientist to head our Battery Analytics team, which plays a critical role in shaping the performance, safety, and profitability of our EV fleet. This leader will manage a team of ~8 data scientists and analysts, owning the end-to-end analytics strategy: from data collection, cleaning, and modelling to deployment of insights into operations. The role requires a balance of technical excellence, leadership capability, and strong business acumen to translate analytics into actionable outcomes.

Responsibilities:

-Lead the battery analytics program to predict battery degradation, Remaining Useful Life (RUL), performance drift, and failure modes across a large-scale EV fleet.

-Develop and deploy machine learning and Bayesian models for anomaly detection, predictive maintenance, and optimization of charging/discharging cycles.

-Integrate telemetry, IoT, and fleet operations data with external datasets (traffic, weather, route conditions) to maximize vehicle uptime and profitability.

-Drive end-to-end MLOps processes: data pipelines, feature engineering, model training, validation, deployment, and monitoring in production.

-Work closely with engineering, operations, and product teams to ensure insights are actionable and directly improve fleet performance.

-Provide thought leadership in advanced analytics, guiding the executive team on opportunities to monetize data, reduce downtime, and optimize asset utilization.

-Mentor and develop a high-performing team of junior data scientists, fostering a culture of learning, collaboration, and innovation.

-Represent the company in external forums, research collaborations, and vendor discussions on analytics, AI, and EV technology.

-Participate in design reviews to provide valuable input on the validation requirements and strategies.

-Stay up to date with the latest advancements and technologies in electric vehicle charging to continuously improve the validation process.

-Destructive tests of Chargers and estimation of life hours and reliability of circuits.

-Undertake Factory Acceptance Test and Site Acceptance Test in accordance with the ITP by working in sync with all stakeholders and issue reports.

Qualification:
B.E./B. Tech in computer science, Information technology or applicable degree

Experience :
5-8 years of experience in data science or applied machine learning, with at least 2 years in a leadership/mentorship role.

Skills:

-Proven expertise in time-series modelling, predictive maintenance, survival analysis, or reliability engineering.

-Strong proficiency in Python, SQL, and ML libraries (scikit-learn, PyTorch, TensorFlow).

-Experience with cloud-based data platforms (AWS, Azure, GCP) and big data ecosystems (PySpark).

-Solid understanding of battery technologies (preferably NMC and LFP chemistries) and their degradation/thermal behaviours.

-Demonstrated ability to manage cross-functional projects, aligning data science outputs with business objectives.

-Excellent communication and storytelling skills to influence senior stakeholders.

-Knowledge of Bayesian inference, probabilistic programming (PyMC, Stan, Prophet), and advanced statistical modelling.

-Experience with optimization libraries (Google OR-Tools, PuLP, Gurobi) for fleet and charging scheduling.

-Exposure to IoT/edge analytics, sensor fusion, and signal processing.

-Familiarity with battery management systems (BMS) data, electrochemical models, or EV thermal management.

-Track record of contributing to open-source projects in data science/ML.

Location: Delhi, Gurugram

Interested candidate should have EV Industry knowledge.

Please drop your CV