Senior Data Scientist - Credit Bureau Data, La Grange-au-Rupt

Job Description: A data-driven financial services company is seeking a Senior Data Scientist

with deep expertise in U.S. consumer credit bureau data to support the development of analytics products and research initiatives focused on credit behavior, scoring, and financial access. This role is well-suited for someone who has a strong background in statistics, machine learning, and in-depth familiarity with U.S. credit reporting structures , particularly those used by the major national credit data providers.

Location:

Washington, D.C. (preferred) or New York, NY

Salary:

Up to 150k base + bonus

Responsibilities:

Analyze large-scale structured and semi-structured datasets to identify insights that guide product development and inform business strategy.

Perform detailed profiling of consumer credit data, integrating traditional data with emerging or non-traditional sources.

Interpret complex file layouts, schemas, and metadata from multiple credit data providers— and manage the inconsistencies across them.

Conduct advanced exploratory data analyses to surface patterns in credit behavior and payment trends.

Lead evaluations for new models and products, including techniques such as back-testing and rejection inference.

Enhance and maintain analytics monitoring frameworks and build data dashboards for internal use.

Work closely with engineering teams to bring analytical tools and models into scalable production environments.

Qualifications:

Master’s or PhD in a quantitative field such as data science, statistics, engineering, or a related discipline.

3–5+ years of experience working with U.S. consumer credit data and applying data science methodologies in an applied setting.

Deep familiarity with credit data structures, attributes, and formatting used by national credit data providers, including knowledge of variances in how data is reported and stored.

Demonstrated ability to perform rigorous, large-scale analytics using Python

Proven experience with SAS

Proven history of leveraging technical skills and domain knowledge to create actionable insights and business value.

Familiarity with alternative data sources and their integration into traditional credit data frameworks.

Experience designing or deploying ML models in a financial services or risk-based context (preferred)

#J-18808-Ljbffr