Senior Analyst, Business Data

NIGHTINGALE EDUCATION LLC SOLE MB•Salt Lake City, UT

About The Position

The Senior Data Analyst designs and delivers predictive, prescriptive, and diagnostic analyses to inform strategic business decisions. The role owns the full analytical lifecycle—from hypothesis formation and modeling through executive insight delivery and outcome measurement—and serves as an authoritative source for metric definitions and data-driven recommendations across the organization. The ideal candidate is a self-directed analytical thinker who works effectively in ambiguous environments, translates complex findings into actionable recommendations, and sets a high analytical standard for the team and enterprise.

Requirements

Bachelor’s degree in Statistics, Computer Science, Data Science, Mathematics, or a related quantitative field.
At least 5 years designing and delivering predictive or prescriptive analytics in cross-functional business environments.
Track record of translating analytical findings into measurable business impact and driving decisions and outcomes, not just reporting.
Experience with statistical experimentation, including A/B testing and causal inference, and hypothesis-driven problem-solving.
Advanced SQL proficiency and experience with cloud-based data warehouses such as Snowflake, Redshift, or BigQuery.
Proficiency in Python or R for statistical modeling and data manipulation.
Experience with statistical modeling libraries such as scikit-learn, statsmodels, or equivalent.
Familiarity with data transformation tools and practices, such as dbt or similar ELT frameworks.
Proficiency in visualization platforms such as Tableau or Power BI, including the ability to build analytical dashboards that drive decisions.

Nice To Haves

Advanced degree (MS or PhD) in a quantitative field.

Responsibilities

Design, build, and validate statistical and machine learning models to forecast outcomes, identify risk, and generate recommendations; own the full model lifecycle.
Frame business problems as testable hypotheses and design and execute analytical frameworks, including A/B tests, causal inference, and regression analysis.
Translate findings into recommendations for leadership that are supported by documented methodology and tied to measurable business outcomes.
Assist with KPI and metric definitions across the organization, partnering with business analysts to make metrics measurable, meaningful, and methodologically sound; lead their validation, refinement, and standardization over time.
Own data quality for analytical outputs by implementing monitoring frameworks and validation processes, resolving root causes, and establishing and maintaining quality standards.
Ensure analytical outputs adhere to data governance standards and promote consistency in metric definitions, methodology, and reporting; serve as a governance checkpoint before artifacts reach leadership.
Serve as a source of analytical interpretation, ensure analyses are rigorous and conclusions defensible, and push back constructively when requests lack needed rigor.
Document analytical methodologies, assumptions, model logic, and limitations to support reproducibility, auditability, and knowledge transfer.
Elevate business users’ analytical capabilities through training, guidance, and tool adoption support.
Lead analytics-focused projects end-to-end, including hypothesis and methodology design, implementation, and impact measurement; scope analytical work, define success criteria, and manage timelines and cross-team dependencies.