Financial Services - Senior - Data Scientist - EDGE
Listed on 2026-06-23
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IT/Tech
Data Analyst, Data Engineering, Data Scientist
Location:
New York, Boston, Philadelphia, Iselin, Hoboken, Stamford, Hartford, Albany, Washington, McLean, Arlington, Baltimore, Charlotte, Raleigh, Miami, Boca Raton, Orlando, Tampa, Jacksonville, Cleveland, Columbus, Cincinnati, Akron, Detroit, Grand Rapids, Toledo, Indianapolis, Chicago, Dallas, Houston, Minneapolis, Austin, San Antonio, Nashville, Memphis, St. Louis, Kansas City, New Orleans, Milwaukee, Des Moines, Oklahoma City, Tulsa, Rogers, Atlanta, Portland
At EY, we’re all in to shape your future with confidence.
We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.
Tax – Financial Services Organization – Other Tax – Data Scientist - Senior Will you shape the future or will the future shape you? The opportunityEY is a leader in serving the global financial services marketplace and the only professional services firm with a separate business unit dedicated to the financial services industry – the Financial Services Organization (FSO). Our focused model and bold ambition have put us at the center of events that continue to reshape and redefine our industry, working side by side with a range of clients from our most venerable institutions to dynamic new entrants across Banking and Capital Markets, Wealth and Asset Management, Insurance, and Real Estate, Hospitality and Construction.
Our purpose is to help build a financial services industry in which financial institutions are trusted and flourish, and the global economy is healthy, growing, and secure. If you have a passion for rallying together to solve complex challenges, then come join our dynamic FSO team!
Our Financial Services EY EDGE practice is made up of a team of professionals providing dedicated tax technical services to both US and global clients. EDGE stands for Exceptional Delivery and Growth Engine because this team operates in a technical environment with deep process and service delivery experience that distinguishes EY in the marketplace.
Join our Tax Technology and Transformation Team as a Data Scientist Senior, where you will be part of a technology organization that develops and maintains innovative solutions for our client-serving Tax professionals. You will have the opportunity to partner with Tax stakeholders to analyze complex datasets, design and develop advanced data science solutions, and deliver actionable insights using modern Azure-based data and analytics platforms.
In this role, you will leverage tools such as Azure Data Services and Power BI to support data exploration, model deployment, and analytical storytelling.
Key Responsibilities
- Comprehend and translate business requirements in the Tax domain into analytical problem statements
- Partner with business stakeholders, data engineers, and architects to design end-to-end data science and analytics solutions
- Explore, analyze, and prepare structured and semi-structured data for advanced analytics and modeling
- Develop data features and transformations in collaboration with data engineering teams
- Expose analytical insights to end users through Power BI dashboards, APIs, or other modern visualization platforms
- Write complex SQL queries to extract and analyze data across multiple source systems
- Identify data quality issues, assess data limitations, and recommend remediation approaches
- Perform end-to-end data validation and model testing
- Document analytical approaches, assumptions, methodologies, and results for both technical and non-technical audiences
- Strong experience with data science and analytics using Python, R, or similar analytical programming languages
- Experience working with Azure-based data platforms (e.g., Azure SQL, Azure Data Lake, Azure Synapse)
- Strong SQL skills with experience querying large, complex datasets
- Experience applying statistical analysis, machine learning, and predictive modeling techniques in a production environment
- Knowledge of data engineering concepts, ETL processes, and collaboration with data pipeline teams
- Understanding of data quality, data governance, and master data management…
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