Senior Applied Data Scientist - Personalization (RecSys)

Quick Facts

• Role: Senior Applied Data Scientist (Personalization / RecSys)

• Pay range: $98,000.00 - $176,000.00

Description

You will collaborate with data scientists, machine learning engineers, and product managers to build and augment AI-driven digital recommendation and personalization products. The role focuses on deep learning and statistical/optimization-driven development: exploring data, implementing algorithmic solutions, deploying to production, and analyzing performance and trade-offs. You are also expected to follow best-practice software design and contribute through code reviews, documentation, and communication with both technical and non-technical audiences.

Responsibilities

• Perform data exploration and analysis

• Implement algorithmic solutions based on specifications

• Push solutions to production and analyze performance and trade-offs

• Follow Agile principles and best-practice software design

• Participate in code reviews; create maintainable, well-tested code with documentation

• Present work to technical and non-technical peers

• Translate business priorities and goals into data science requirements and solutions

Requirements

• MS or PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, Operations Research, or relevant work experience

• 3+ years developing machine learning models using deep learning frameworks such as PyTorch or JAX

• Experience building recommendation, personalization, search, ranking, or retrieval systems at scale

• Strong programming skills in Python and SQL

• Demonstrated experience with optimization, statistics, probability, and experimental design

• Experience evaluating models via offline analysis on large-scale datasets and online experimentation, including statistical analysis and interpretation of results

• Knowledge of large-scale data processing and analytics platforms such as Spark

• Extensive experience leveraging generative AI tools to accelerate development, experimentation, and model delivery

• Ability to communicate complex technical concepts to both technical and non-technical audiences

• Demonstrated ability to translate business problems into scalable data science solutions

• Self-driven, results-oriented, collaborative, and able to meet tight deadlines

Benefits

• Comprehensive health benefits (medical, vision, dental, life insurance, and more) for eligible team members and dependents

• 401(k)

• Employee discount

• Short-term disability and long-term disability

• Paid sick leave, paid national holidays, and paid vacation