Senior Business Data Analyst

Nightingale Education Group

. Design, build, and validate statistical and machine learning models to forecast outcomes, identify risk, and generate recommendations .

Posted 11/5/2026full-timeRemote • Utah • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and validating statistical and machine learning models, with a strong focus on translating analytical findings into actionable business insights. Proficient in managing the full model lifecycle and ensuring adherence to data governance standards.

Highest-signal resume keywords

Statistical ModelingA/B TestingAdvanced SQL ProficiencyPython or R ProficiencyPredictive Analytics

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical ExperimentationCausal InferenceData Quality ManagementKPI DefinitionHypothesis-Driven Problem Solving

Soft Skills

LeadershipCross-Team CollaborationTraining and Guidance

Tools & Technologies

SnowflakeRedshiftBigQueryScikit-learnTableauPower BIDbt

Certifications & Qualifications

Bachelor’s Degree in StatisticsBachelor’s Degree in Computer ScienceBachelor’s Degree in Data ScienceBachelor’s Degree in MathematicsAdvanced Degree (MS/PhD) Preferred

Industry Keywords

Predictive AnalyticsPrescriptive AnalyticsData GovernanceAnalytical OutputsMetric Validation

Tech Stack

Tools & technologies

Amazon RedshiftBigQueryCloudPythonScikit-LearnSnowflakeSQLTableau

About the role

Key responsibilities & impact

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
Design and execute A/B tests, causal inference, and regression analyses
Translate findings into insight-driven recommendations for leadership
Assist with KPI and metric definitions across the organization
Lead metric validation, refinement, and standardization
Own data quality for analytical outputs
Implement monitoring frameworks, validation processes, and root-cause resolution
Ensure analytical outputs adhere to data governance standards
Serve as the analytical interpretation and governance resource
Document methodologies, assumptions, model logic, and limitations
Train and guide business users in analytical capabilities and tool adoption
Lead analytics-focused projects end-to-end, including methodology design, implementation, and impact measurement
Scope analytical work, define success criteria, and manage timelines and cross-team dependencies

Requirements

What you’ll need

Bachelor’s degree in Statistics, Computer Science, Data Science, Mathematics, or related quantitative field
5+ years designing and delivering predictive or prescriptive analytics in cross-functional business environments
Track record of translating analytical findings into measurable business impact
Experience with statistical experimentation, including A/B testing and causal inference
Hypothesis-driven problem-solving experience
Advanced SQL proficiency
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 scikit-learn, statsmodels, or equivalent libraries
Familiarity with data transformation tools and ELT frameworks such as dbt
Proficiency in Tableau or Power BI
Advanced degree (MS/PhD) strongly preferred