A globally acclaimed Physical AI and Connected Vehicle technology leader developing advanced onboard intelligence and connected telematics platforms ("smart black box") for the modern automotive ecosystem.
Leveraging massive-scale data ingestion and sophisticated machine learning, the company delivers real-time behavioral analytics and predictive insights utilized by major automotive OEMs, Tier-1 suppliers, and massive enterprise fleets across four continents.
With an unrivaled technological moat and strong institutional backing from a premier private equity group, the organization tackles complex algorithmic challenges spanning billions of sensory data points daily.
The company is located in the Sharon region and operates on a hybrid model with two days working from home
Role Description-
- Serving as a Senior Data Scientist (Hands-on IC), reporting directly to the VP Data Science and taking complete end-to-end ownership of sophisticated DS/ML initiatives—from problem framing and hypothesis generation to production deployment and long-term monitoring.
- Architecting and developing machine learning solutions operating over massive-scale Vehicle Telemetry, Multi-sensor signals, and Fault data processing billions of daily data points with high noise and weak/delayed ground truth labels.
- Applying diverse modeling paradigms, combining Classical Machine Learning, Advanced Statistical Modeling, Survival Analysis, and Deep Learning architectures tailored for raw multivariate time-series signals.
- Designing, integrating, and deploying cutting-edge LLM-based pipelines and Agentic workflows into live production systems.
- Building and optimizing scalable Data Pipelines, Distributed Computing workflows, and ML Infrastructure in tight alignment with production engineering teams.
- Monitoring, evaluating, and maintaining model health, latency, and predictive performance in mission-critical customer-facing production environments.
Requirements-
- Master’s Degree (M.Sc.) or Ph.D. in a technical/quantitative field (Computer Science, Data Science, Electrical Engineering, Statistics, Physics, or Mathematics) – Mandatory
- 7+ years of total experience as a Data Scientist – Mandatory
- 5+ years of practical, post-academic Data Science experience in the industry – Mandatory
- Strong, advanced software engineering capabilities in Python (scientific stack, ML libraries, and production-grade code) – Mandatory
- Proven track record deploying complex ML / DL models to live Production environments – Mandatory
- Deep expertise working with large-scale datasets, noisy sensory signals, time-series telemetry, or distributed data frameworks – Significant Advantage
- Hands-on experience with modern GenAI, LLMs, and Agentic frameworks in production – Advantage
- Background in Automotive, IoT, or Physical AI ecosystems – Advantage
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