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About the Role
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.
Responsibilities
- Design, build, and validate statistical and machine learning models to forecast outcomes, identify risk, and generate recommendations.
- Frame business problems as testable hypotheses.
- Design and execute analytical frameworks including A/B tests, causal inference, and regression analysis to generate rigorous conclusions.
- Translate findings into insight-driven recommendations for leadership, tied to measurable business outcomes and supported by documented methodology.
- Assist with KPI and metric definitions across the organization, partnering with business analysts to define measurable, meaningful, and methodologically sound metrics.
- Lead validation, refinement, and standardization of metrics over time.
- Own data quality for all analytical outputs, implementing monitoring frameworks, validation processes, and root-cause resolution.
- Establish and maintain data quality standards.
- Ensure all analytical outputs adhere to data governance standards, promoting consistency in metric definitions, methodology, and reporting.
- Serve as a governance checkpoint before artifacts reach leadership.
- Serve as the go-to source for analytical interpretation, ensuring analyses are rigorous, conclusions defensible, and recommendations actionable.
- Constructively push back when analytical requests lack needed rigor.
- Document analytical methodologies, assumptions, model logic, and limitations to ensure reproducibility, auditability, and knowledge transfer.
- Elevate analytical capabilities of business users through training, guidance, and tool adoption support.
- Lead analytics-focused projects end-to-end: hypothesis and methodology design, implementation, and impact measurement.
- Scope analytical work, define success criteria, and manage timelines and cross-team dependencies.
Requirements
- 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.
Skills
- Advanced SQL proficiency
- 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)
- Ability to build analytical dashboards that drive decisions
Location
- OSC Utah - Salt Lake City, UT
Experience Level
- Senior
Education Level
- Bachelor’s degree in Statistics, Computer Science, Data Science, Mathematics, or related quantitative field
- Advanced degree (MS/PhD) strongly preferred
Salary/Compensations
- Undisclosed