Data Scientist

Primary Responsibilities

• Develop recurring reports and analytics supporting capital, sales, commissions, intercompany transactions, and risk management, and create ad hoc reports and analyses for the direct manager and C-suite.
• Build, maintain, enhance, and troubleshoot Power BI dashboards and reports, including Power Query transformations, DAX measures, data models, and reporting logic.
• Prepare and distribute a biweekly Risk Committee reporting package highlighting portfolio performance, emerging risks, exceptions, trends, and areas requiring management attention.
• Use financial modeling, regression analysis, statistical techniques, and advanced Excel tools to evaluate business drivers, support dynamic pricing, and contribute to revenue growth.
• Extract, clean, reconcile, and analyze data from SQL databases, accounting systems, Excel workbooks, CSV files, and other applications to identify trends, anomalies, risks, and performance drivers.
• Partner with stakeholders to define reporting requirements and key performance indicators, validate data accuracy, automate recurring processes, and maintain reporting documentation.

Minimum Qualifications

• Bachelor's degree in Computer Science and at least three years of professional experience in data analytics, business intelligence, financial analytics, or a related role.
• Advanced proficiency in Microsoft Excel and SQL, including complex queries, joins, common table expressions, aggregations, pivot tables, financial modeling, data validation, and large-dataset analysis.
• Hands-on experience building and maintaining Power BI dashboards and reports using Power Query, DAX, relational data models, and calculated measures.
• Strong understanding of relational databases, data structures, data quality controls, reporting methodologies, and business intelligence concepts.
• Experience applying statistical analysis, regression, forecasting, trend analysis, and variance analysis to business or financial data.
• Ability to translate business requirements into accurate reports, dashboards, key performance indicators, and actionable recommendations, and clearly present findings to senior management and C-suite stakeholders.
• Experience with accounting systems and financial data, combined with strong analytical, organizational, problem-solving, communication, multitasking, and time-management skills.

Preferred Qualifications

• Experience with Python or R for data manipulation, statistical analysis, automation, or model development.
• Experience in financial services, lending, portfolio or risk analytics, ETL processes, data warehouses, APIs, or cloud-based data platforms.