Lenovo

1. Performance Analysis & Monitoring
a) Analyze live metrics for existing AI projects features and strategic initiatives, rapidly diagnosing any deviations or anomalies in KPIs.
b) Conduct A/B test evaluations and cohort analyses to forecast and compare potential future feature/strategy outcomes.
2. Dashboard Development & Visualization
a) Design, develop, and maintain interactive dashboards using BI tools (e.g., Tableau, Power BI, Looker) to visualize key metrics, AI model outputs, and operational KPIs for stakeholders.
b) Optimize dashboard performance and usability, ensuring real-time data updates, intuitive navigation, and responsive layouts.
c) Enable self-service analytics by providing training materials, documentation or even ChatBI.
3. Support Business and Uncover New Opportunity
a) Engage deeply with cross-functional stakeholders (e.g., sales, operations, marketing), gathering detailed research questions and translating them into analytical projects.
b) Deliver concise, data-backed reports and presentations that guide decision-making.
c) Use exploratory analysis to uncover new business opportunities and recommend strategic data-driven roadmaps.
4. Data Solution Design & Implementation
a) Partner with Product Managers and Engineering teams to define optimization product strategies and design predictive or prescriptive models.
b) Take ownership of end-to-end deployment—wrapping models in reproducible pipelines, overseeing validation, and monitoring live performance.
c) Design data analysis functionality with latest AI tech or tools to improve business operation efficiency.
5. Data Governance & Prompt Engineering Ability
a) Coordinate with Data Engineering and IT to ensure seamless data ingestion, quality controls, and governance standards.
b) Able to use and optimize the prompts to GenAI models to achieve better.