Lead Data Scientist: Personalization & Recommenders (Transformers)

Capital One; McLean (VA); On-site; USD 197,000 - 225,000; Full time

Job summary

Capital One is seeking a Data Scientist in McLean, VA to help design and implement large-scale recommender systems. You will use transformers, LLMs, and reinforcement learning on billions of transactions and interactions to improve personalized experiences across digital products.

You will collaborate with engineering and product teams to deploy scalable, low-latency systems, evaluate campaigns, and push the boundaries of generative recommendations and cross-domain personalization.

Qualifications

• Bachelor’s degree in a quantitative field with several years of data analytics experience.
• Master’s or MBA with quantitative concentration plus several years of analytics experience.
• PhD in a quantitative field with at least one year of analytics experience.

Responsibilities

• Design and develop state-of-the-art recommender systems using transformers, large language models (LLMs), and reinforcement learning.
• Advance personalization through sequence modeling, multimodal learning, and contextual decision-making.
• Build and fine-tune foundation models trained on large-scale customer interaction data.
• Apply reinforcement learning to optimize long-term user engagement and business outcomes.
• Build evaluation frameworks to measure the efficacy of campaigns and recommendations.
• Collaborate with engineering and product teams to deploy scalable, low-latency systems.
• Drive innovation in areas such as generative recommendations and cross-domain personalization.

Skills

Transformers

LLMs

Reinforcement learning

Python

PyTorch

Distributed training

SQL

AWS

Data science workflows

Experimentation

Education

Bachelor's + 6 yrs analytics

Master's or MBA quantitative +4 yrs

PhD +1 yr

Tools

Python

PyTorch

TensorFlow

SQL

AWS

Job description

Capital One is seeking a Data Scientist in McLean, VA to help design and implement large-scale recommender systems. You will use transformers, LLMs, and reinforcement learning on billions of transactions and interactions to improve personalized experiences across digital products.

You will collaborate with engineering and product teams to deploy scalable, low-latency systems, evaluate campaigns, and push the boundaries of generative recommendations and cross-domain personalization.