Sr. Manager, AI Innovation.

Role overview Lead hands-on data science and AI work, taking solutions from exploration and modeling through production deployment. The role covers predictive decision systems, generative AI, language models, agentic applications, and the engineering practices needed to make these capabilities useful and maintainable in real settings.

Responsibilities - Explore and prepare structured, semi-structured, and unstructured data, including text, voice, and event streams. - Build, evaluate, and refine models for prediction, scoring, risk detection, prioritization, and decision support. - Develop interpretable scores, risk bands, thresholds, and intervention logic where decisions need to be explained. - Turn prototypes into production-ready capabilities, balancing model quality with stability, usability, and maintainability. - Apply data science and machine learning tools such as Python, SQL, Spark, Databricks, MLflow, scikit-learn, XGBoost, or PyTorch. - Communicate model assumptions, limits, and trade-offs to both technical and non-technical stakeholders while providing technical guidance.

Requirements - Senior-level, hands-on experience in data science and AI solution development. - Ability to perform exploratory and statistical analysis, assess data quality, engineer features, train models, and evaluate performance. - Strong engineering discipline, including reproducible work, version control, testing, documentation, and maintainable code. - Judgment to balance predictive performance, transparency, stability, and business usefulness. - Ability to work independently while guiding technical decisions and modeling practices.