Lead Software Engineer - Data Science and Platform Engineering

Software Lead - Data Science

Platform & Data Engineering - Own the end‑to‑end data architecture: ingestion from BMS/SCADA/EMS, time‑series storage, feature store, model serving, and secure APIs.

Establish telemetry pipelines with strong data quality, lineage, observability, and SLA adherence.

 

Analytics & Modeling (Usage & Performance Correlation) - Translate usage signals (Current/C‑rate, SoC, temperature/thermal profiles, cycle vs calendar aging) into performance metrics (SOH, capacity fade, impedance growth, efficiency, safety risk). Build predictive models for RUL, anomaly/failure detection, state estimation (SOC/SOH/SOx); quantify uncertainty and provide explainability. Apply Bayesian optimization and multivariate prognostics for early cycle‑life prediction and parameter tuning.

 

1. Battery User Experience

Develop on‑device models and energy accounting for SW features; architect end‑to‑end solutions to improve perceived battery life, charging and thermal performance. Build user‑facing systems and interfaces that educate users/operators and guide behavior for healthier usage patterns.

 

1. Products, Dashboards & Decisioning

Deliver operator dashboards with actionable KPIs: performance & availability, safety alerts, degradation indicators, dispatch optimization signals.

Partner with EMS/controls on algorithmic hooks for energy arbitrage, peak shifting, compliance, and event analytics.

 

1. Reliability, MLOps & Delivery

 

Own MLOps: experiment tracking, CI/CD for models, monitoring (drift/latency), rollback/OTA updates; drive “model‑in‑production” culture. 

Lead QA and site integration for new releases; validate against field data and simulation before rollout. 

 

Bachelor’s/master’s in computer science, Data Science, Electrical/Power/Electrochemistry, or related field. 

8 to 10 Yrs.

Experience Level

Senior Level