Q
Senior Data Scientist
·Israel
On-siteFull-timeData ScienceAutomotiveFleet Management
Join a physical AI company developing vehicle health management solutions for commercial fleets. Own data science projects from problem framing and data exploration through modeling, deployment, monitoring, and production support.
Responsibilities
- Own projects end to end, including stakeholder discussions, problem framing, exploration, modeling, validation, deployment, and monitoring
- Build predictive and prescriptive models using large-scale vehicle telemetry, diagnostics, and fault data
- Design, build, and maintain scalable, reproducible, and well-tested data pipelines
- Operate workflows for training, validation, inference, and ongoing evaluation
- Deploy solutions with automated testing, environment configuration, monitoring, and troubleshooting
- Select and explain appropriate methods, including gradient boosting, survival analysis, and deep learning
- Design realistic evaluations and apply proprietary validation methods
- Develop and integrate agentic and LLM-based flows that explain findings and recommend actions
- Investigate failures across data, models, workflows, and production systems
- Present findings, trade-offs, and results to business stakeholders and executive leadership
- Raise technical standards through reviews, mentorship, and shared practices as a senior individual contributor
Requirements
- Master’s degree in computer science, engineering, statistics, physics, applied mathematics, or another related quantitative field
- At least 8 years of industry experience in data science or machine learning
- Experience deploying, monitoring, maintaining, retraining, and troubleshooting machine learning solutions in production
- Strong experience building reliable, performant, and tested pipelines for very large datasets
- Experience with Spark, distributed computing, SQL, and modern big data platforms
- Experience with automated testing and deployment, cloud systems, workflow orchestration, monitoring, and production troubleshooting
- Production experience delivering LLM or agentic applications, including evaluation, guardrails, and cost and latency trade-offs
- Strong knowledge of statistics, experimental design, classical machine learning, and deep learning
- Excellent Python skills and fluency with PyTorch
- Very good English communication skills, including presentations to business stakeholders and executive audiences
- Ability to lead projects independently, make decisions under ambiguity, and work across data science, data engineering, deployment, and production systems
Nice to have
- PhD in a relevant field
- Experience with Databricks
- Automotive, telematics, IoT, predictive maintenance, or industrial systems experience
- Experience with anomaly detection, remaining useful life, or failure prediction using weak or delayed labels
- Experience designing and operating end-to-end machine learning systems
Benefits
- Work on difficult, high-impact problems involving real vehicle fleets across four continents
- Broad ownership across data, modeling, deployment, and production systems
- Fast-moving environment with startup-style decision-making and substantial scale
- Work in a senior team that values initiative, pragmatism, and technical quality