Senior Data Scientist, Consumer Identity Machine Learning

Capital One; New York (NY); On-site; USD 145,100 - 165,600; Full time

Job summary

Capital One is seeking a Senior Data Scientist for Consumer Identity ML. You will develop real-time models leveraging billions of customer data to personalize experiences, fight fraud, and improve outcomes across marketing, servicing, and product experiences.

You will collaborate with product and engineering teams, write Python-based data science code, and validate models end-to-end in scalable production systems serving tens of millions of customers.

Qualifications

• Bachelor’s Degree in a quantitative field plus 2 years of data analytics experience or Master’s Degree/MBA with quantitative focus.
• Master’s Degree in a quantitative field or MBA with quantitative concentration; PhD in STEM preferred.

Responsibilities

• Build machine learning models through all phases of development and work with engineering to productionize at scale for 50 million customers.

Skills

Python

PyTorch

Scala

R

SQL

Natural Language Processing

AWS

Machine Learning

Education

Bachelor’s Degree in a quantitative field

Master’s Degree in a quantitative field or MBA with a quantitative concentration

Tools

Spark

Job description

Senior Data Scientist, Consumer Identity Machine Learning

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

Consumer Identity ML is the data science and machine learning team inside Capital One’s AI foundation organization. We deliver real-time, personalized, intelligent customer experiences in Capital One’s suite of award-winning digital products, including our website, mobile app, emails, chatbot, and beyond. We partner closely with our product and engineering teams to build the data and modeling platforms crucial to the deep understanding of customers that enables our applications to delight them by adapting to their needs.

As part of Consumer ML, you will:

• Explore billions of clickstream events to discover the patterns in customer behavior, and use those patterns to model key customer outcomes

• Develop the real-time models that use vast amounts of customer data to anticipate customers’ needs and deliver the right options at the right time

• Develop the models that ensure our most important customer data is accurate, fighting fraud and other bad behavior, while enabling seamless digital experiences across all our products

Role Description

In Consumer Identity ML, you will work at all phases of the data science life cycle, including:

• Build machine learning models through all phases of development, from design through training, evaluation and validation, and partner with engineering teams to improve operationalization in scalable and resilient production systems that serve 50 million customers.

• Partner closely with a variety of business and product teams across Capital One to conduct the experiments that guide improvements to customer experiences and business outcomes in domains like marketing, servicing and fraud prevention.

• Write software (Python, e.g.) to collect, explore, visualize and analyze numerical and textual data (billions of customer transactions, clicks, payments, etc.) using tools like Spark.

The Ideal Candidate is:

• 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 back tested 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.

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 2 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

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 (Science, Technology, Engineering, or Mathematics)

• At least 1 year of experience working with AWS

• At least 2 years’ experience in Python, PyTorch, Scala, or R

• At least 2 years’ experience with machine learning

• At least 2 years’ experience with SQL

• At least 2 years’ experience working with natural language processing

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.

McLean, VA: $133,000 – $151,800 for Sr Assoc, Data Science
New York, NY: $145,100 – $165,600 for Sr Assoc, Data Science San Jose, CA: $145,100 – $165,600 for Sr Assoc, 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 . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

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 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, California 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.

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Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).