Senior Data Analyst
6 days ago
Senior Data Analyst (Finance & Accounting)About the Role
We're looking for a Senior Data Analyst to turn large, messy financial datasets into clear, actionable insights. You'll partner with Finance, Accounting, and Engineering to design robust analyses, build decision-ready dashboards, and drive reconciliation accuracy across bank files, GL feeds, and sub-ledgers.
What You'll Do
- Own analytics for finance workflows:
Depository Account Reconciliation (DAR), AP/AR, Daily Income Journal (DIJ), revenue recognition, month-end close, variance analysis. - Data wrangling & modeling:
Ingest, clean, and model data from BAI/BAI2 bank files, GL (Oracle/Yardi/MRI/NetSuite), PMS/ERP exports, payment gateways, and data lakes. - EDA → inference:
Frame hypotheses, run exploratory/statistical analyses, and deliver clear narratives with quantified impact (trends, anomalies, outliers, correlations). - Reconciliation analytics:
Build matching logic (exact/fuzzy/multi-key), exception buckets, and root-cause drill-downs for unmatched transactions. - Metrics & dashboards:
Define and publish finance KPIs (auto-match %, write-offs, DSO, unapplied cash, exceptions aging) via curated semantic layers and BI dashboards. - Data quality stewardship:
Establish checks, controls, and monitoring (balance checks, duplicate detection, schema drift, completeness/timeliness tests). - Stakeholder enablement:
Translate CFO/Controller questions into analysis plans; document assumptions; present findings to execs with crisp recommendations. - Automation partnership:
Collaborate with data engineering to productionize repeatable pipelines, models, and audits; create specs for dbt/ETL jobs. - Compliance-aware analysis:
Ensure work products support
SOX
controls and align with
US GAAP
; maintain reproducible, auditable notebooks and artifacts.
Must-Have Qualifications
- 5–8+ years in data analysis/analytics (at least 3 years in
Finance/Accounting
analytics). - Strong SQL
(window functions, CTEs, query optimization) and
Python
(pandas, NumPy; statsmodels/scikit-learn for light modeling). - Proven experience with
GL/AP/AR
data, bank statement structures (e.g.,
BAI/BAI2
), and reconciliation/matching logic. - Hands-on with a modern BI tool (Power BI / Tableau / Looker / Superset) and version-controlled analytics (git).
- Excellent storytelling: converts ambiguous business questions into testable analyses and executive-friendly outputs.
- Solid grasp of accounting concepts (journal entries, trial balance, revenue vs. receipts, accruals/deferrals) and
controls mindset
.
Nice to Have
- dbt, Airflow/Prefect, Dagster; Snowflake/BigQuery/Redshift; AWS (S3, Glue, Athena, Lambda).
- Experience with
anomaly detection
, fuzzy matching (record linkage), and rule-based + ML hybrid matching. - Familiarity with
SOX
,
GAAP
, audit evidence, and finance close calendars. - Exposure to payments/settlement data, PMS/ERP integrations, or RPA/agentic automations.
- Basic proficiency with GitHub Actions/CI for analytics artifacts.
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