below marketmost similar roles pay hereabove market
This role pays more than
58%
of similar roles. Most pay
$175,131–$246,150
— the blue band above.
At the midpoint, this role pays about
$211k
versus about
$211k
for comparable roles.
Based on 240 similar postings.
Employer
About Capital One Financial
Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking
Capital One Financial currently has
2107 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 1107 roles with salary data.
Manager, Data Science - AI Foundations joins the AI Foundations Specialist Models Data Science team to build and ship scalable architecture and AI/ML solutions for a mobile app. You will partner with cross-functional teams to deliver features like dynamic personalized experiences and digital assistant interactions. Your daily work involves experimenting with emerging generative AI technologies, specifically focusing on Natural Language Processing to harness Large Language Models. You will build, train, evaluate, and validate models through all development phases, ensuring they are operationalized in resilient production systems. The role requires expertise in Pytorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, and VectorDBs. You will solve complex problems involving huge volumes of numeric and textual data to improve how customers interact with their money.
What does a Data Science Manager earn?
Median $211200 from 43 postings across 13 companies.
Build and ship scalable AI/ML solutions and architectures for the mobile app.
Adapt and fine-tune Large Language Models (LLMs) for customer-facing applications.
Develop machine learning models through all phases of design, training, evaluation, and validation.
Operationalize models into scalable and resilient production systems serving millions of customers.
Use technologies like Pytorch, AWS Ultraclusters, Hugging Face, and LangChain to analyze large datasets.
Translate complex technical work into tangible business goals for non-technical stakeholders.
Research and evaluate emerging generative AI technologies to create next-generation customer experiences.
What we're looking for
Must have a Bachelor's in a quantitative field plus 6 years of data analytics experience, a Master's plus 4 years, or a PhD plus 1 year.
Must have at least 1 year of experience leveraging open source programming languages for large scale data analysis.
Must have at least 1 year of experience working with machine learning.
Must have at least 1 year of experience utilizing relational databases.
Must have experience training language models or large computer vision models with expertise in subdomains like RLHF or explainability.
Must have an engineering mindset with a track record of delivering models at scale for training and inference.
Must have hands-on experience working with LLMs and solutions using open-source tools and cloud computing platforms.
PhD in a STEM field (preferred); at least 4 years of experience in Python, Scala, or R (preferred); at least 4 years of experience with machine learning (preferred); at least 4 years of experience with SQL (preferred); experience working with AWS (preferred).
Python
SQL
AWS
Pytorch
Hugging Face
LangChain
Lightning
VectorDBs
Natural Language Processing
Large Language Models
Machine Learning
Scala
R
Relational Databases
RLHF
Self-supervised Learning
Model Risk Compliance