Manager, Data Scientist -Advanced Recommenders and Personalization Systems (Transformers, LLMs & Reinforcement Learning)
$179k - $205k • McLean, VA • Full-time
Posted 1mo ago
Job Location
McLean, VA
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
We are building the next generation of large-scale reinforcement learning based recommender systems and arbitration engines that will power personalized experiences across marketing, customer servicing, and digital products. This is a high-impact initiative central to our platform, leveraging rich credit and customer behavioral data from tens of millions of customers to deliver intelligent, real-time experiences across our digital experiences, including Mobile, Web, and Email. You will help shape a foundational system that reaches a vast portion of the U.S. population, influencing how millions of people discover, decide, and engage across financial and lifestyle experiences.
Responsibilities
- Design and develop state-of-the-art recommender systems using transformers, LLMs, and reinforcement learning.
- Advance personalization through sequence modeling, multi-modal 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 state-of-the-art evaluation frameworks to measure the efficacy of campaigns and recommendation systems.
- Collaborate with engineering and product teams to deploy scalable, production-grade, low-latency systems.
- Drive innovation in emerging areas such as generative recommendations, conversational systems, and cross-domain personalization.
Requirements
- Customer first mindset, with a passion for doing the right thing for customers.
- Innovative approach, continually researching and evaluating emerging technologies and state-of-the-art methods.
- Creative problem-solver, comfortable defining and tackling big, undefined problems.
- Leadership qualities, challenging conventional thinking and driving improvements.
- Technical proficiency with open-source languages and developing data science solutions using open-source tools and cloud platforms.
- Strong statistical understanding, including model building, validation, and interpretation.
- Expertise in handling and analyzing large-scale datasets from various sources.
- Strong background in machine learning, deep learning, and recommender systems.
- Hands-on experience with transformers, LLMs, or reinforcement learning.
- Experience working with large-scale datasets and distributed training.
- Solid programming skills in Python and modern ML frameworks (e.g., PyTorch, TensorFlow).
- Ability to translate research into impactful, real-world systems.
- Bachelor's Degree in a quantitative field plus 6 years of experience, or Master's Degree plus 4 years of experience, or PhD plus 1 year of experience.
- 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.
- PhD in a STEM field plus 3 years of experience in data analytics (preferred).
- At least 1 year of experience working with AWS (preferred).
- At least 4 years’ experience in Python, Scala, or R for large scale data analysis (preferred).
- At least 4 years’ experience with machine learning (preferred).
- At least 4 years’ experience with SQL (preferred).