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LeadFull-timePythonData ScienceAIML
Salary Range
$120,000 - $180,000 /year
Key Responsibilities
- →Lead structured discovery sessions with Finance, FP&A, Accounting, and Product to define measurable business outcomes.
- →Translate business questions into data definitions, dimensional models, transformation logic, and semantic layer requirements.
- →Prototype and build Power BI dashboards and semantic models to validate logic before engineering productionization.
- →Develop advanced DAX measures, KPI frameworks, and scenario modeling logic for financial and operational reporting.
- →Partner closely with data engineers to ensure scalable pipeline design aligned with reporting and analytics needs.
- →Support statistical analysis and model output interpretation in partnership with data science cross-functional teammates.
- →Own metric definitions, documentation, governance standards, and data dictionaries to ensure enterprise consistency.
- →Design data validation, reconciliation, and UAT frameworks to ensure financial data integrity and audit readiness.
- →Identify opportunities to automate recurring reporting, improve process efficiency, and reduce manual analysis.
- →Operate as a cross-functional advisor who balances business strategy, data architecture awareness, and technical feasibility.
Requirements
- ✓7+ years of experience in business analytics, analytics engineering, management consulting, or a related role.
- ✓Strong hands-on expertise in Power BI (DAX, semantic modeling, performance tuning, KPI design).
- ✓Solid proficiency in SQL for data exploration, validation, and transformation logic design.
- ✓Strong understanding of dimensional modeling, relational schemas, and data warehouse concepts.
- ✓Ability to translate ambiguous business problems into structured analytical frameworks and technical specifications.
- ✓Experience working directly with senior stakeholders in Finance, FP&A, or corporate strategy functions.
- ✓Comfort interpreting model outputs and understanding basic statistical concepts (variance, regression, forecasting assumptions).
- ✓Experience supporting enterprise financial reporting or project-based accounting environments.
- ✓Exposure to Microsoft Fabric, modern Lakehouse architectures, or analytics engineering workflows.
- ✓Experience collaborating on ML-enabled use cases such as classification, forecasting, or anomaly detection.
- ✓Background in regulated or compliance-driven environments.
- ✓Familiarity with Python for light analysis, validation, or automation tasks.
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