Manager, Data Scientist - Credit Review

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 relational databases, 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 In Capital One’s Credit Review Models, Data and Innovative Solutions team, we defend the company against model failures and find new ways of making better decisions with models. We use our statistics, software engineering, and business expertise to drive the best outcomes in both Risk Management and the Enterprise. We understand that we can’t prepare for tomorrow by focusing on today, so we invest in the future: investing in new skills, building better tools, and maintaining a network of trusted partners. We partner with best‑in‑class data scientists, analysts, credit risk management experts, and engineers to innovate solutions that directly impact the company’s bottom line in a meaningful way. We do it all in a collaborative environment that values individual insight, encourages each associate to take on new responsibilities, promotes continuous learning, and rewards innovation. Role Description In this role, you will: Leverage a broad stack of technologies, such as Python, Conda, AWS, H2O, Spark, and more, to reveal the insights hidden within huge volumes of numeric and textual data. Build statistical and machine learning models to challenge the models in production. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. Partner with a cross‑functional team of data scientists, credit risk experts, and product managers to deliver a product customers love. Ideal Candidate 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. 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. Basic Qualifications Degree and experience. 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 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. 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 databases. Preferred Qualifications PhD in a STEM field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics. At least 4 years’ experience in Python, Scala, or R for large‑scale data analysis. At least 4 years’ experience with machine learning. At least 4 years’ experience with predictive modeling. Benefits 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. Eligibility varies based on full or part‑time status, exempt or non‑exempt status, and management level. Salary Charlotte, NC: $179,400‑$204,700 for Mgr, Data Science McLean, VA: $197,300‑$225,100 for Mgr, Data Science Plano, TX: $179,400‑$204,700 for Mgr, Data Science Richmond, VA: $179,400‑$204,700 for Mgr, Data Science Riverwoods, IL: $179,400‑$204,700 for 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. Equal Employment Opportunity Capital One is an equal opportunity employer (EOE, including disability/veteran) committed to non‑discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23‑A of the New York Correction Law; San Francisco, CA Police Code Article 49, Sections 4901‑4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. #J-18808-Ljbffr