Data Scientist: BI Dashboards, Risk & Financial Analytics

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

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