- Manage, coach, and develop two Team Leads and four Analysts, setting roles, quality standards, feedback, and accountability.
- Prioritize analytical demand based on business impact, urgency, data readiness, and capacity.
- Own the enterprise analytical agenda and resource plan while remaining hands-on in priority delivery.
- Translate business questions into statistical analyses, predictive models, experiments, dashboards, forecasts, scenario models, and recommendations.
- Evaluate and communicate model performance, assumptions, limitations, and material changes in results.
- Advise senior leaders on findings, uncertainty, and trade-offs, and challenge business assumptions and analytical methods.
- Establish consistent metric definitions, technical evaluation, documentation, and review practices.
- Partner with data engineering and business teams to improve data quality, automate recurring work, expand self-service analytics, and retire redundant reporting.
- Review demand, decision usefulness, and recurring quality issues, and track agreed improvements.
PythonSQLBusiness Intelligence