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Principal Associate, Data Scientist - Retail Bank Valuations Data ScienceCapital One • Virginia, Minnesota, United States
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Principal Associate, Data Scientist - Retail Bank Valuations Data Science

Capital One
  • US
    Virginia, Minnesota, United States
  • US
    Virginia, Minnesota, United States
Jetzt Bewerben

Über

Principal Associate, Data Scientist – Retail Bank Valuations & 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 The Marketing & Valuations Data Science Team in the Retail Bank builds models that improve marketing efficiency and drive account growth via intelligent targeting, measurement, segmentation, and customer value modeling. We do data and model pipelining, machine learning, and well‑managed model operations using Python and ML libraries in our tech stacks. Role Description In this role you will be building the next generation of customer valuations models for the Retail Bank that improve marketing efficiency and drive account growth via intelligent targeting, measurement, and segmentation. Work closely with subject matter experts to deliver flexible, well‑managed models that perform well under a variety of economic conditions. Translate business goals into data science solutions and communicate with senior stakeholders. Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation. Explore next‑generation model architectures (e.g. embeddings, sequence models) to unlock value in our marketing efficiency. Ideal Candidate Technical: You’re comfortable with open‑source languages and are passionate about developing further. You have hands‑on experience with software engineering techniques and developing end‑to‑end model pipelines in Python. Statistically‑minded: You are experienced in various machine learning algorithms and predictive solutions. 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. A storyteller: You are effective in communicating technical details to a variety of audiences. 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: Bachelor’s Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 5 years of experience performing data analytics. 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 3 years of experience performing data analytics. PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field).
Preferred Qualifications Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in “STEM” field. At least 3 years’ experience in Python. At least 3 years’ experience with machine learning, including XGBoost. At least 3 years’ experience with SQL. At least 1 year’s experience in open‑source programming languages for large‑scale data analysis. Experience with next‑generation model architectures such as embeddings, sequence models. Compensation & Benefits 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. McLean, VA: $161,800 – $184,600 This role is also eligible to earn performance‑based incentive compensation, which may include cash bonus(es) and/or long‑term incentives (LTI). Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well‑being. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. EEO & Equal Opportunity Capital One is an equal opportunity employer (EOE, including disability/vet) 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.
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  • Virginia, Minnesota, United States

Sprachkenntnisse

  • English
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