Data Scientist

StevenDouglas; Miami (FL); On-site; USD 85,000 - 120,000; Full time

Job summary

StevenDouglas seeks a data analytics professional to develop recurring reports and analytics supporting capital, sales, commissions, intercompany transactions, and risk management, and to create ad hoc analyses for the direct manager and C-suite.

You'll build and troubleshoot Power BI dashboards, perform transformations, data models, and DAX measures, prepare biweekly risk committee packages, and use SQL and Excel to extract, clean, and analyze data across systems, partnering with stakeholders

Qualifications

• Bachelor's degree in Computer Science with at least three years in data analytics or BI.
• Advanced proficiency in Excel and SQL, including complex queries and data validation.
• Hands-on experience building Power BI dashboards using Power Query, DAX, and relational models.
• Strong knowledge of data quality, BI concepts, and reporting methodologies.

Responsibilities

• Develop recurring reports and analytics for capital, sales, commissions, intercompany, and risk management.
• Build and enhance Power BI dashboards, including data models and reporting logic.
• Prepare biweekly risk committee reporting on portfolio performance, risks, trends, and management touchpoints.
• Extract, clean, reconcile, and analyze data from SQL databases and various sources to identify trends and drivers.
• Collaborate with stakeholders to define KPIs, automate processes, and maintain reporting documentation.

Skills

Excel

SQL

Power BI

Data analysis

Education

Bachelor's degree in Computer Science

Tools

Power BI

Power Query

DAX

SQL

Job description

• 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.