Director, Data Scientist - Generative AI Systems

Capital One; McLean (VA); On-site; USD 269,100 - 307,200; Full time

Benefits offered by this job

Comprehensive health benefits

Performance-based bonuses

Inclusive work environment

Job summary

Capital One in McLean, VA is seeking a Data Scientist to lead innovative AI-driven analytics, focusing on Natural Language Processing and machine learning. You will collaborate with a team to develop data science solutions catering to customer needs. The position requires a Bachelor's degree in a relevant quantitative field and multiple years of experience in data analytics and programming. A competitive salary is offered, ranging from $269,100 to $307,200 annually, alongside performance-based incentives.

Qualifications

• Bachelor's degree in Statistics, Economics, or a related field.
• 4+ years of experience leveraging open-source programming languages for data analysis.
• Experience working with machine learning and relational databases.

Responsibilities

• Partner with cross-functional teams to deliver AI-powered products.
• Leverage technologies to analyze large volumes of data.
• Build and operationalize machine learning and NLP models.

Skills

Natural Language Processing

Machine Learning

Data Analysis

Open-source programming languages

Interpersonal Skills

Education

Bachelor's Degree in a quantitative field

Master's Degree in a quantitative field

PhD in a quantitative field

Tools

Python

AWS

Pytorch

Job description

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 Generative AI Systems (Genesis) team within Card Data Science builds state‑of‑art, generative AI‑based solutions for dialogue, text summarization, reading comprehension, speech recognition, image/document processing as well as time‑series sequencing modeling. We partner with product, tech and design teams to deliver internal applications based on these solutions that drive efficiency in our business and data analytics teams, as well as customer‑facing applications that enhance the customer experience. You will lead a seasoned group of natural language processing (NLP), speech, and computer vision specialists, experimenting with emerging technologies in generative AI, delivering software implementing these technologies, and contributing research to major NLP and AI/ML conferences.

Role Description

In this role, you will:

• Partner with a cross‑functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI powered products that change how customers interact with their money.
• Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, VectorDBs, and more — to reveal the insights hidden within huge volumes of numeric and textual data.
• Be the expert in Natural Language Processing (NLP) to harness the power of Large Language Models (LLMs), adapt and finetune them for customer facing applications and features.
• Build machine learning and NLP models through all phases of development, from design through training, evaluation, and validation; partnering with engineering teams to operationalize them in scalable and resilient production systems that serve 80+ million customers.
• Flex your interpersonal skills to translate the complexity of your work into tangible business goals.

The Ideal Candidate is:

• Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers.
• 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 leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond.
• 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.

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 9 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 7 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 4 years of experience performing data analytics
• At least 4 years of experience leveraging open source programming languages for large scale data analysis
• At least 4 years of experience working with machine learning
• At least 4 years of experience utilizing relational databases

Preferred Qualifications

• PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 5 years of experience in data analytics
• At least 1 year of experience working with AWS
• At least 3 years of experience managing people
• At least 5 years of experience in Python, Scala, or R for large scale data analysis
• At least 5 years of experience with machine learning

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: $269,100 - $307,200 for Dir, Data Science

New York, NY: $293,600 - $335,100 for Dir, 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 Capital One Careers website. Eligibility varies based on full or part‑time status, exempt or non‑exempt status, and management level.

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.