Data Scientist
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Job Description
Data Scientist building Databricks revenue reporting and pipelines for AgencyBloc's life and health insurance agency platform. Automating reconciliation, forecasting, dashboards, and governed GTM metrics.
Responsibilities:
- Rebuild core revenue reporting, starting with the consolidated GTM book, in AgencyBloc's Databricks lakehouse
- Build and maintain data pipelines from HubSpot, Sage Intacct, and other GTM systems into the lakehouse through a curated, report-ready gold layer
- Migrate department-built reporting tools, such as Client Success dashboards, onto governed lakehouse data
- Replace manual, credential-dependent refreshes and hand-built spreadsheets with scheduled, automated Python and SQL jobs
- Reconcile lakehouse outputs against HubSpot and legacy reports deal by deal, identify omitted records, and correct logic
- Run automated reports alongside existing manual processes until historical numbers align
- Build data quality checks for completeness, duplicates, and schema drift, and resolve issues at the source
- Build dashboards and data models for self-service GTM reporting
- Support pipeline and revenue forecasting with clean data and build statistical or predictive models as the platform matures
- Calculate and validate sales commissions and bonuses from system data and document payout rules
- Document calculation logic for bookings, expansion, new logo, renewals, and upsells
- Align metric definitions across Sales, Client Success, and FP&A
- Maintain the data dictionary and follow AI and Data Governance standards for access, lineage, and documentation
- Gather stakeholder requirements and select appropriate implementation approaches
- Participate in commissions and revenue reviews with sales and executive leadership
- Present findings and recommendations to individual contributors and executive audiences
- Anticipate questions, proactively flag issues, and carry work through to completion
Requirements:
- Bachelor's or master's degree in Data Science, Statistics, Computer Science, Information Systems/Management, Business Analytics, Finance, or a related field, or equivalent experience
- 3+ years in a data analyst, analytics engineering, or BI role, building production reporting rather than one-off analysis
- Strong SQL skills: complex joins, window functions, and query tuning against relational or lakehouse data
- Working proficiency in Python for data transformation and automating recurring reports
- Demonstrated experience automating manual reporting processes, with measurable time saved or errors removed
- Experience reconciling data across systems and tracing discrepancies to the record level
- Hands-on dashboard and data modeling experience with Databricks AI/BI, Tableau, Power BI, or similar
- Clear written and verbal communication, including explaining numbers and their limits to senior leaders
- Self-directed working style with the judgment to ask the right questions and carry work through without step-by-step direction
- Databricks experience, including Delta Lake, Unity Catalog, Workflows/Jobs, and notebooks
- HubSpot data model and reporting experience, including deals, pipelines, companies, and custom objects
- Experience with ERP or billing data, such as Sage Intacct invoice detail and ARR calculations
- Exposure to forecasting, statistical analysis, or predictive modeling in Python, R, or SAS
- Experience with sales compensation or commission calculations
- Familiarity with data governance practices, including standardized metric definitions, data dictionaries, lineage, and role-based access
- Version control with Git and shell scripting for scheduled, auditable data jobs
- Background in B2B SaaS, insurance, financial services, or another regulated-data environment
- Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States.
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