Manager, Data Scientist - Model Risk Office

Capital One; Chicago (IL); On-site; USD 140,000 - 200,000; Full time

Benefits offered by this job

Comprehensive health benefits

Competitive salary

Inclusive benefits supporting well-being

Job summary

A leading financial institution is seeking a skilled candidate to join their data science team in Chicago. This role involves partnering with various teams to identify risks and build machine learning models. Candidates should possess a quantitative degree and extensive experience in data analysis, open-source programming, and machine learning practices. The position offers a competitive benefits package and supports diverse well-being initiatives, making it appealing to potential applicants.

Qualifications

• At least 1 year of experience leveraging open source programming languages for large scale data analysis.
• At least 4 years’ experience with machine learning, including GenAI.
• Experience in building or validating models related to fraud detection or digital marketing.
• A Bachelor's Degree in a quantitative field plus 6 years of experience performing data analytics; or a Master's Degree with 4 years; or a PhD with 1 year; or STEM PhD with 3 years of data analytics.

Responsibilities

• Partner with cross-functional teams to identify and quantify risks.
• Build machine learning models for production.
• Validate models across multiple business domains.
• Stay current on state-of-the-art methods and technologies and apply them to real-world problems.

Skills

Open source programming languages

Machine learning

Data retrieval and analysis

Statistical analysis

Interpersonal skills

Education

Bachelor's Degree in a quantitative field

Master's Degree or MBA in a quantitative concentration

PhD in a quantitative field

Tools

Python

AWS

Relational databases

Vector databases

PyTorch

Job description

* Partner with a cross-functional team of data scientists, software engineers, and product managers to identify and quantify risks associated with models* Leverage a broad stack of technologies — from foundational frameworks (PyTorch, Hugging Face), to orchestration tools (LangChain, Vector Databases) to LLMOps, observability platforms, and more — to reveal the insights hidden within huge volumes of multi-modal data* Build machine learning models to challenge “champion models” that are deployed in production today and contribute to the model governance framework for the next generation of models* Validate a wide variety of models across multiple business domains within our Enterprise Services division, and flex your interpersonal skills to present how identified model risks could impact the business to executives.* Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.* Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.* Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.* Statistically-minded. You’ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.* A data guru. “Big data” doesn’t faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.* Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:* At least 1 year of experience leveraging open source programming languages for large scale data analysis* At least 1 year of experience working with machine learning* At least 1 year of experience utilizing relational or vector databases* A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 years of experience performing data analytics* A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 4 years of experience performing data analytics* A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience performing data analytics* PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics* At least 1 year of experience working with AWS* At least 4 years’ experience in Python, Scala, or R for large scale data analysis* At least 4 years’ experience with machine learning, including GenAI* At least 4 years’ experience building or validating models related to fraud detection, digital marketing, cybersecurity, or sensitive data detection.Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.