Job Description

Responsibilities:Seeking a data analyst with strong SQL and Python, Tableau skills to deliver clear, actionable insights for finance stakeholders; the role emphasizes analytics over machine learning and requires excellent communication with non-technical audiences.ResponsibilitiesQuery and transform financial datasets using advanced SQL to support reporting, reconciliation, trend analysis, and ad‑hoc investigations.Build maintainable Python scripts/notebooks for data cleaning, validation, calculations (e.g., accruals, allocations), and repeatable analytics workflows.Create concise visual summaries and narratives for business partners; translate data findings into recommendations and next steps.Partner with FP&A, accounting, and product teams to gather requirements, define metrics, and ensure data accuracy and auditability.Document data sources, logic, and assumptions; standardize templates and ensure version control and reproducibility.Required QualificationsProficient in SQL (joins, CTEs, window functions, performance tuning) across large, normalized financial datasets.Hands-on Python for data analysis (Pandas, NumPy), file I/O (CSV/Excel), and basic automation; emphasis on readability and reliability.Strong communication skills: clear writing, structured storytelling, and stakeholder-facing presentation of findings.Financial analytics experience (e.g., revenue/expense trends, variance analysis, reconciliations, KPIs) without reliance on machine learning.Solid Excel skills (pivot tables, lookups) and comfort working with requirements trackers and documentation.Nice to HaveExperience with BI/reporting tools (Tableau/Power BI/Looker) for dashboarding and self-serve reporting.Familiarity with finance concepts (P&L, balance sheet, cash flow, bookings/billings, cost allocations).Version control (Git) and basic task automation/scheduling.Success IndicatorsAccurate, timely analyses with well-documented assumptions and reproducible SQL/Python.Clear executive-ready deliverables that drive decisions and reduce time-to-insight.Fewer data defects via proactive validation and reconciliation across sources.

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