Senior Associate, Data Scientist - Anti-Money Laundering, Modeling and Advanced Data Analytics

OverviewSenior Associate, Data Scientist - Anti-Money Laundering, Modeling and Advanced Data AnalyticsJoin to apply for the Senior Associate, Data Scientist - Anti-Money Laundering, Modeling and Advanced Data Analytics role at Capital One.Role DescriptionIn this role, you will be part of the Modeling and Advanced Data Insights (MADI) team focused on Anti-Money Laundering (AML). You will help build machine learning and AI models to strengthen risk management and AML programs, with emphasis on supporting and developing List Screening models and expanding innovative approaches within Compliance & Ethics.ResponsibilitiesPartner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers loveLeverage technologies such as Python, Conda, AWS, H2O, Spark, and more to reveal insights in large numeric and textual datasetsBuild machine learning models through all phases of development: design, training, evaluation, validation, and implementationThe Ideal CandidateInnovative: researches and applies emerging technologies and state-of-the-art methodsCreative: defines big problems, asks questions, and shares new ideasTechnical: experience with open-source languages and developing data science solutions using open-source tools and cloud platformsStatistically-minded: experience with modeling, validation, backtesting, and interpreting metrics like confusion matrices, ROC curves; experience with clustering, classification, sentiment analysis, time series, and deep learningA data guru: can retrieve, combine, and analyze data from diverse sources and structuresBasic QualificationsCurrently has, or is in the process of obtaining, a quantitative degree with an expectation to complete by start date: Bachelor's Degree in Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related field plus 2 years of data analytics experience; or Master's Degree in a quantitative field or MBA with quantitative concentrationPreferred QualificationsMaster's Degree in STEM, or PhD in STEMExperience working with AWSAt least 2 years' experience in Python, Scala, or RAt least 2 years' experience with machine learningAt least 2 years' experience with SQLCapital 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. Salaries are provided for candidates hired to work within the specified locations and reflect the amount Capital One is willing to pay at the time of posting. Part-time salaries will be prorated.McLean, VA: $133,000 - $151,800 for Sr Assoc, Data ScienceRichmond, VA: $120,900 - $138,000 for Sr Assoc, Data ScienceRiverwoods, IL: $120,900 - $138,000 for Sr Assoc, Data ScienceOther locations: pay ranges align with local market rates.This role is eligible for performance-based incentives, which may include cash bonuses and/or long-term incentives. Capital One offers comprehensive benefits; eligibility varies by status and level. For details, visit the Capital One Careers website.This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable laws. Capital One maintains a drug-free workplace and complies with applicable background-check laws.If you require accommodations during the application process, please contact Capital One Recruiting at 1-800-304-9102 or RecruitingAccommodation@capitalone.com. For technical support or questions about Capital One's recruiting process, email Careers@capitalone.com.Capital One does not endorse or guarantee third-party products or services accessed via this site. Capital One may post roles internationally (e.g., Capital One Canada, Capital One Europe, Capital One Philippines Service Corp.).Seniority levelAssociateEmployment typeFull-timeJob functionEngineering and Information TechnologyJ-18808-Ljbffr