Manager, Data Science - Consumer Identity Machine Learning

Hobbsnews; San Jose (CA); On-site; USD 215,200 - 245,600; Full time

Job summary

Capital One is seeking a Manager, Data Science - Consumer Identity Machine Learning to lead real‑time modelling that personalises experiences for millions of customers. You will build scalable data platforms, experiment with cross‑functional teams and translate analytics into actionable customer outcomes.

You will work with Python, Spark and open‑source tools, guiding model development from design to production while collaborating with product and engineering teams across the company.

Qualifications

• Bachelor’s in a quantitative field plus 6 years analytics experience.
• Master’s in a quantitative field or MBA with a quantitative concentration plus 4 years analytics.
• PhD in a quantitative field plus 1 year 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.

Responsibilities

• Explore billions of click‑stream events to discover patterns in customer behaviour and use those patterns to model key customer outcomes.
• Develop real‑time models that use vast amounts of customer data to anticipate customers’ needs and deliver the right options at the right time.
• Develop models that ensure our most important customer data is accurate, fighting fraud and other bad behaviour while enabling seamless digital experiences across all our products.
• Build machine‑learning models through all phases of development, from design through training, evaluation and validation, and partner with engineering teams to improve operationalisation 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 such as marketing, servicing and fraud prevention.
• Write software (Python, etc.) to collect, explore, visualise and analyse numerical and textual data using tools like Spark.

Skills

Innovative

Creative

Technical

Statistically-minded

Data guru

Education

Bachelor’s degree in a quantitative field

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

PhD in a quantitative field

Tools

Python

Spark

SQL

AWS

Job description

Manager, Data Science - Consumer Identity Machine Learning

Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalising every credit card offer using statistical modelling 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 organisation. 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 modelling platforms crucial to the deep understanding of customers that enables our applications to delight them by adapting to their needs.

Roles and Responsibilities

• Explore billions of click‑stream events to discover patterns in customer behaviour and use those patterns to model key customer outcomes.
• Develop real‑time models that use vast amounts of customer data to anticipate customers’ needs and deliver the right options at the right time.
• Develop models that ensure our most important customer data is accurate, fighting fraud and other bad behaviour while enabling seamless digital experiences across all our products.
• Build machine‑learning models through all phases of development, from design through training, evaluation and validation, and partner with engineering teams to improve operationalisation 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 such as marketing, servicing and fraud prevention.
• Write software (Python, etc.) to collect, explore, visualise and analyse numerical and textual data (billions of customer transactions, clicks, payments, etc.) using tools like Spark.

Ideal Candidate

• Innovative: continually research and evaluate emerging technologies, stay current on state‑of‑the‑art methods, technologies and applications and seek opportunities to apply them.
• Creative: thrive on bringing definition to big, undefined problems, love asking questions and pushing hard to find answers, and are not afraid to share new ideas.
• Technical: comfortable with open‑source languages and passionate about developing further; have hands‑on experience developing data‑science solutions using open‑source tools and cloud computing platforms.
• Statistically‑minded: built models, validated them and back‑tested them; know how to interpret a confusion matrix or ROC curve; have experience with clustering, classification, sentiment analysis, time series and deep learning.
• A data guru: “big data” doesn’t faze you; have the skills to retrieve, combine and analyse data from a variety of sources and structures; know that 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:
  • 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.
  • 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.
  • 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 utilising relational databases.

Preferred Qualifications

• PhD in a STEM field (Science, Technology, Engineering or Mathematics) plus 3 years of experience in data analytics.
• At least 1 year of experience working with AWS.
• At least 4 years of experience in Python, Scala or R for large‑scale data analysis.
• At least 4 years of experience with machine learning.
• At least 4 years of experience with SQL.

Compensation and Benefits

The minimum and maximum full‑time annual salaries for this role are listed below by location. Salaries are solely for candidates hired to perform work within one of these locations and will be reflected in the offer letter.

McLean, VA: $197,300 – $225,100; New York, NY: $215,200 – $245,600; San Francisco, CA: $215,200 – $245,600; San Jose, CA: $215,200 – $245,600.

This role is eligible to earn performance‑based incentive compensation, including cash bonus(es) and/or long‑term incentives (LTI) which may 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.

Legal and Company Information

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

Capital One is an equal‑opportunity employer (EOE, including disability and veteran). We are committed to non‑discrimination in compliance with applicable federal, state and local laws. Capital One promotes a drug‑free workplace.

Accommodation: If you require an accommodation, please contact Capital One Recruiting at 1‑800‑304‑9102 or email [e-mail]. All information you provide will be kept confidential and used only as required for reasonable accommodations.