About Careertakes

👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Financial Services.

Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.

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What You’ll Do

You will join a cross-functional team building next-generation credit decisioning and scoring systems. In this Senior Associate Data Scientist role you will:

• Partner with data scientists, software engineers, and product managers to design and deliver production-ready models and analytics.
• Develop, validate, and deploy machine learning models across the full lifecycle: problem definition, feature engineering, training, evaluation, validation, and monitoring.
• Work with large, structured and unstructured datasets and alternative data sources to improve credit products and decisioning.
• Leverage tools and platforms such as Python, Conda, Snowflake, AWS, H2O, and Spark to scale modeling and data pipelines.
• Translate technical results into clear recommendations for business and product teams; communicate trade-offs, risk, and performance.
• Contribute to reproducible, tested model implementations and support model governance, validation, and documentation.

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Qualifications

Basic (required)

• Bachelor’s degree in a quantitative field (Statistics, Economics, Mathematics, Computer Science, Operations Research, Analytics, or related) OR in-progress with degree completion expected by start date.
• Minimum 2 years of professional experience performing data analytics or data science work.
• Hands-on experience building and validating machine learning models (classification, clustering, time series, or deep learning).
• Practical experience with Python and SQL; familiarity with at least one of Scala or R is a plus.
• Comfortable working with large datasets and common data engineering patterns.

Preferred

• Master’s or PhD in a STEM field or an MBA with a quantitative concentration.
• 2+ years using cloud platforms and tools (AWS preferred) and modern data warehouses (e.g., Snowflake).
• Experience with model deployment, monitoring, and production ML tooling (H2O, Spark, MLOps practices).
• Background in credit decisioning, financial risk, or related financial-services modeling.
• Strong statistical foundation (model validation, backtesting, ROC/confusion matrix interpretation).

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Compensation & Location

• Location: Chicago, IL (authoritative)
• Employment type: Full-time
• Salary range for candidates working in Chicago, IL: $123,300 - $140,700 per year.
• This role may be eligible for performance-based incentive compensation (bonuses and/or long-term incentives) and a comprehensive benefits package.

Note: Actual pay offered will be determined by the Confidential Client and reflected in any offer letter. The Confidential Client may consider sponsorship for qualified applicants.

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Why You’ll Love This Role

• Work at the intersection of data, engineering, and product to influence credit products that reach millions of customers.
• Gain experience designing models that operate at scale and impact real-time decisioning systems.
• Collaborative, fast-paced environment focused on experimentation, sound model governance, and continuous improvement.
• Access to modern tooling (Python, Snowflake, AWS, Spark) and opportunities for technical growth and mentorship.

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Legal & Hiring Notes

• Confidential Client and Careertakes are committed to lawful, inclusive hiring practices consistent with applicable federal, state, and local laws.
• Criminal history will be considered in a manner consistent with applicable laws. Reasonable accommodations are available for applicants with disabilities; if you need an accommodation during the hiring process, please contact Careertakes.
• Visa sponsorship may be considered for qualified candidates; individual circumstances will be evaluated.

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Equal Opportunity & Hiring Transparency

Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.

If you have questions about how your data is used, please contact us directly.