· 6+ years of experience in data science, machine learning, or applied AI with a track record of delivering business-impacting solutions
· Strong programming skills in Python, PySpark, and SQL
· Solid grounding in statistics, machine learning, experimentation, and model evaluation
· Hands-on experience with Databricks for exploratory analysis, model development, and reproducible ML workflows; familiarity with MLflow is strongly preferred
· Demonstrated experience with time series modeling, forecasting, anomaly detection, and/or sequential data problems
· Experience working with IoT, sensor, telemetry, or other operational data sources
· Strong data engineering capability, including data wrangling at scale, feature pipeline design, dataset preparation, data quality troubleshooting, and support for production-ready analytical workflows
· Experience creating data products or analytics products intended for repeated use
· Experience designing baselines, features, evaluation frameworks, and error analysis approaches for real-world AI/ML use cases
· Strong ability to work across GitHub and Azure DevOps workflows, including pull requests, version control, and delivery tracking
· Demonstrated ability to communicate clearly with technical and non-technical stakeholders and to influence product decisions with evidence
· Experience partnering cross-functionally with engineering, product, and business teams to move from problem framing to production decision-making