Staff Data Scientist

About the role

Staff Data Scientist at Netradyne leads evaluation and analytics for AI/ML features in fleet safety solutions. Focuses on building rigorous evaluation frameworks, KPI audits, and statistical rigor to ensure trustworthy, decision‑ready AI systems. Owns offline/online evaluation pipelines, golden datasets, and benchmarking standards. Conducts large‑scale studies, error and bias analysis, and segmentation to uncover failure modes. Designs experiments, A/B tests, and controlled rollouts, ensuring statistical correctness. Builds dashboards, automation, and reproducible analytics pipelines to scale audits. Translates insights into actionable recommendations for engineering, product, and leadership. Mentors junior scientists on experiment design and storytelling. Requires strong probability, statistics, Python, SQL, and cloud platform experience (AWS).

What you’ll do

• Own evaluation framework design, implementation, maintenance
• Define, validate, evolve KPIs, success metrics, audit methods
• Conduct deep error, bias, segmentation analysis
• Own golden datasets, validation protocols, benchmarking standards
• Perform large-scale analytical studies on feature performance
• Translate findings into actionable insights for engineering, product, leadership
• Design and review experiments, A/B tests, controlled rollouts
• Ensure statistical correctness: bias, variance, confidence, significance
• Monitor post-deployment, detect regressions
• Build and maintain dashboards, automation frameworks for audits
• Improve reproducibility, reliability of analytics pipelines
• Enable self‑serve analytics for broader teams
• Identify gaps in evaluation, metrics, data quality, drive solutions
• Mentor junior data scientists on rigor, experiment design, storytelling

What you’ll bring

• Tech/M.Tech/PhD CS/EE/Stats/Math
• 5+ yrs data science/analytics experience
• Strong probability, statistics, estimation theory
• Python programming, OOP, algorithms, data structures
• SQL deep expertise, NoSQL knowledge
• Data visualization, storytelling
• Excellent communication

Nice to have

• Exposure to cloud platforms (AWS Kinesis, EKS, autoscaling)
• Build lightweight web/service components with Python frameworks (Flask, Django)
• Experience with large-scale, noisy, real-world datasets

Skills

Education

Bachelor/Master/PhD