Senior Manager, Data Science - Financial Services

Senior Manager, Data Science

Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making. As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

Team Description: As a Data Scientist at Capital One's Auto Finance business, you'll be part of a high performing modeling and analytics team that's leading the next wave of disruption at a whole new scale. Our team has a relentless focus on the craft of modeling and innovation, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives. You'll drive the heart of business by working on an array of impactful and exciting applications like chat bot, customer summarization, message recommendation, and next best actions via Generative AI.

Role Description: In this role, you will:

• Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
• Leverage a broad stack of technologies — Python, AWS, LLM and more — to reveal the insights hidden within huge volumes of structured and unstructured data
• Build Generative AI models and products through all phases of development, from design through training, evaluation, validation, implementation, monitoring and risk governance
• Flex your interpersonal skills to translate the complexity of your work into tangible business goals

The Ideal Candidate is:

• Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing.
• 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.
• A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond.
• Technical. You're comfortable with open-source languages, LLM prompting/fine-tuning and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.

Basic Qualifications:

• 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:
• A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 7 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 5 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 2 years of experience performing data analytics
• At least 2 years of experience leveraging open source programming languages for large scale data analysis
• At least 2 years of experience working with machine learning
• At least 2 years of experience utilizing relational databases

Preferred Qualifications:

• PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 4 years of experience in data analytics
• At least 2 year of experience working with AWS
• At least 2 year of experience managing people
• At least 2 years' experience in LLM training and evaluation
• At least 2 years' experience in GenAI application development
• At least 5 years' experience in Python for large scale data analysis
• At least 5 years' experience with machine learning
• At least 1 year experience working with AWS
• At least 1 year experience managing people
• At least 1 years experience in LLM training and evaluation
• At least 1 years experience in GenAI application development
• At least 3 years experience in Python, Scala, or R for large scale data analysis
• At least 3 years experience with machine learning

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Plano, TX: $209,000 - $238,500 for Sr Mgr, Data Science

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

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 Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.