Analytics Engineer

• Design, build, and maintain forecasting and analytical models that support strategic planning, staffing, and financial decision-making.

• Build and maintain internal tools, automations, and production-grade model deployments that scale the team’s analytical capabilities beyond ad hoc analysis.

• Analyze complex operational and financial datasets to identify trends, risks, and opportunities.

• Provide analytical support for executive leadership by responding to strategic inquiries, special initiatives, and emerging business needs.

• Develop and monitor KPIs across business functions to ensure accurate performance measurement and alignment to goals.

• Translate data into actionable insights through clear reporting, dashboards, and executive-ready presentations.

• Improve and enhance analytical methodologies by incorporating new data sources, testing assumptions, and refining model parameters.

• Partner cross-functionally with Operations, Finance, Marketing, and Legal teams to align forecasts and planning assumptions.

• Conduct variance analysis and support root-cause investigations when results diverge from expectations.

• Uses AI as a productivity and impact multiplier, embedding it into workflows to accelerate analysis, improve output quality, and scale.

• BS or MS in Engineering, Computer Science, Statistics, or related quantitative field.

• 4+ years of experience in data science, engineering, analytics, or forecasting in a corporate environment.

• Demonstrated experience building and maintaining data models that influence operational or financial decisions.

• Strong proficiency in SQL and Python (or R) for data transformation, statistical analysis, machine learning, and automation.

• Familiarity with modern software engineering and cloud practices, including version control (Git), cloud platforms (Azure/AWS), agentic coding tools, containerization, CI/CD, and API development.

• Experience developing dashboards and reports using modern BI tools (Power BI preferred).

• Experience building and maintaining scalable ETL/ELT workflows, including data ingestion, transformation logic, validation checks, and production-ready analytical datasets.

• Advanced quantitative modeling, analytical reasoning, and critical thinking skills.

• Ability to communicate complex analytical concepts to both technical and non-technical audiences.

• Demonstrated ability to manage ambiguity, prioritize effectively, and deliver results in a fast-paced environment.

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