Data Scientist

Performance Evaluation & Oversight

• a) Assess real-time metrics for current AI project features and strategic developments, swiftly identifying any discrepancies or irregularities in KPIs.
• b) Execute A/B testing and cohort analysis to project and compare possible future outcomes for features and strategies.

Dashboard Creation & Data Visualization

• a) Create, develop, and manage interactive dashboards utilizing BI tools (such as Tableau, Power BI, Looker) to illustrate essential metrics, AI model results, and operational KPIs for stakeholders.
• b) Enhance dashboard efficiency and user experience, ensuring real-time data updates, intuitive navigation, and adaptable layouts.
• c) Facilitate self-service analytics by supplying training materials, documentation, or tools like ChatBI.

Business Support & Opportunity Identification

• a) Collaborate extensively with cross-functional teams (including sales, operations, and marketing) to gather comprehensive research inquiries and transform them into analytical projects.
• b) Produce clear, data-driven reports and presentations that inform decision-making processes.
• c) Utilize exploratory analysis to identify new business avenues and propose strategic, data-informed roadmaps.

Data Solution Development & Execution

• a) Work alongside Product Managers and Engineering teams to establish optimization product strategies and design predictive or prescriptive models.
• b) Take full responsibility for end-to-end deployment—encapsulating models in reproducible pipelines, overseeing validation, and monitoring live performance.
• c) Create data analysis functionalities using the latest AI technologies or tools to enhance operational efficiency.

Data Governance & Prompt Engineering Skills

• a) Collaborate with Data Engineering and IT to ensure efficient data ingestion, quality control measures, and adherence to governance standards.
• b) Proficient in utilizing and optimizing prompts for GenAI models to achieve improved outcomes.