Data Scientist Lead
Location: Strongsville, OH or Pittsburgh, PA
Work Mode : 5 Days Onsite
Duration: Contract to Hire
Years Of Exp Required: 14+ Years
Function of the Group: Mitigating Risk
Project : Perform ongoing analysis of fraud trends and emerging schemes through daily monitoring, trend reviews, and deep dives to proactively identify risk patterns. - Design and implement fraud monitoring for new products and capabilities, ensuring timely coverage, risk assessments, and alignment with enterprise fraud frameworks. - Optimize and streamline existing fraud monitoring processes by improving alert logic, reducing noise, and enhancing efficiency through automation and standardization. - Partner with cross?functional domains to develop and enhance advanced pattern detection solutions and countermeasures.
Industry background: Banking / Finance - Data Scientist
Roles and Responsibilities :
- Leverages business / product expertise to rigorously analyze large datasets, improve risk adjusted returns, deliver profitable growth, and communicate conclusions.
- Synthesizes analytical results and develops, recommends, and implements business strategies that improve lending decisions, assist in managing risk, increase revenues, reduce exposure to losses, meet business goals, and improve performance.
- Establishes baselines for strategies and tracks actual performance to expectations.
- Applies predictive models, third party data, and other tools to develop and execute appropriate segmentation and targeting for acquisition and portfolio strategies to provide insight into portfolio risk.
- Manages engagements with internal and external information suppliers ensuring solution is fit for purpose while maintaining appropriate governance and oversight.
- Works with business, credit, data, and model development partners to design, develop, and monitor test designs and analytical reporting to track and enhance strategies.
- Designs / enhances standard reporting suites for regular product / portfolio reviews.
- Collaborates with the line of business, Finance, and Risk partners to assess and establish credit risk appetite and to understand its implications, as well as to establish policies and procedures governing the identification, monitoring, and management of risk appetite.
- Math, statistics, and quantitative analysis background
- Proficiency with SQL, Python or R
- Strong Analytic Mindset and Data Skills
- Tableau, Power BI
- Effective Communication Skills
- Model Development
- Prior banking experience and/or prior anti-fraud experience, especially with digital transaction products (ACH, Wire Transfer, ETC)
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