Senior Analyst, Business Data

The Senior Data Analyst designs and delivers predictive, prescriptive, and diagnostic analyses that inform strategic business decisions. This role owns the full analytical lifecycle — from hypothesis formation and modeling to executive insight delivery and outcome measurement — and serves as the authoritative source for metric definitions and data-driven recommendations across the organization. 

The ideal candidate is a self-directed analytical thinker who thrives in ambiguous environments, translates complex findings into actionable recommendations, and sets the analytical standard for the team and enterprise. 

Key Responsibilities: 

Analysis & Insight Delivery 

• Predictive & Prescriptive Modeling: Design, build, and validate statistical and machine learning models to forecast outcomes, identify risk, and generate recommendations. Own the full model lifecycle. 

• Hypothesis-Driven Analysis: Frame business problems as testable hypotheses. Design and execute analytical frameworks including A/B tests, causal inference, and regression analysis to generate rigorous conclusions. 

• Analytical Recommendations: Translate findings into insight-driven recommendations for leadership. Recommendations must be tied to measurable business outcomes and supported by documented methodology. 

Metric Strategy & Governance 

• Metric Definition: Assist with KPI and metric definitions across the organization. Partner with business analysts to define metrics that are measurable, meaningful, and methodologically sound. Lead validation, refinement, and standardization over time. 

• Data Quality & Integrity: Own data quality for all analytical outputs. Implement monitoring frameworks, validation processes, and root-cause resolution. Establish and maintain quality standards. 

• Governance Compliance: Ensure all analytical outputs adhere to data governance standards. Promote consistency in metric definitions, methodology, and reporting. Serve as governance checkpoint before artifacts reach leadership. 

Partnership & Enablement 

• Analytical Advisory: Serve as the go-to source for analytical interpretation. Ensure analyses are rigorous, conclusions defensible, and recommendations actionable. Push back constructively when requests lack needed rigor. 

• Methodology Documentation: Document analytical methodologies, assumptions, model logic, and limitations to ensure reproducibility, auditability, and knowledge transfer. 

• Training & Capability Building: Elevate analytical capabilities of business users through training, guidance, and tool adoption support. 

• Analytical Project Ownership: Lead analytics-focused projects end-to-end: hypothesis and methodology design, implementation, and impact measurement. Scope analytical work, define success criteria, manage timelines and cross-team dependencies. 

• Education: Bachelor’s degree in Statistics, Computer Science, Data Science, Mathematics, or related quantitative field; advanced degree (MS/PhD) strongly preferred. 

• Experience: 5+ years designing and delivering predictive or prescriptive analytics in cross-functional business environments. Track record of translating analytical findings into measurable business impact — driving decisions and outcomes, not just reporting. Experience with statistical experimentation (A/B testing, causal inference) and hypothesis-driven problem-solving. 

• Technical Skills: Advanced SQL proficiency and experience with cloud-based data warehouses (Snowflake, Redshift, BigQuery). Proficiency in Python or R for statistical modeling and data manipulation. Experience with libraries such as scikit-learn, statsmodels, or equivalent. Familiarity with data transformation tools and practices (e.g., dbt or similar ELT frameworks). Proficiency in visualization platforms (Tableau, Power BI) with ability to build analytical dashboards that drive decisions.