Senior Data Scientist, Search & Recommendations

About the role

As a Senior Data Scientist, Search & Recommendation, you will be a key individual contributor within the AI/ML team responsible for building and improving intelligent search and recommendation systems that power customer and athlete experiences across omnichannel platforms. You will collaborate closely with machine learning engineers, software engineers, product managers, and data engineers to design and deploy models that improve relevance, personalization, ranking, retrieval, and discovery.

Responsibilities

• Design and implement machine learning models for search and recommendation systems, including ranking, retrieval, personalization, and query understanding
• Build ranking and recommendation models using user behavior, embeddings, content signals, and contextual features
• Develop personalization systems that tailor results based on user behavior, preferences, and contextual signals (e.g., location, browsing history)
• Collaborate with data and search engineers to build scalable data pipelines supporting search and recommendation systems
• Partner with software engineers to integrate ML models into production services via APIs
• Design and execute A/B tests to evaluate model performance and business impact
• Monitor offline and online metrics to identify opportunities for improving relevance, ranking, and engagement
• Apply modern ML and GenAI techniques (embeddings, LLM-based approaches) to improve search and discovery experiences
• Contribute to best practices in modeling, experimentation, and production ML systems

Qualifications

• 5+ years of experience in data science, machine learning, or applied AI
• Strong experience with search, recommendation systems, or ranking problems
• Hands-on experience with Elasticsearch and/or Solr
• Strong Python skills and experience with ML frameworks such as TensorFlow or PyTorch
• Experience with large-scale data processing tools such as Spark and distributed systems
• Experience integrating ML models into production systems via APIs
• Experience with experimentation frameworks and A/B testing
• Strong understanding of ML fundamentals: supervised learning, ranking models, embeddings, deep learning
• Exposure to GenAI tools (OpenAI APIs, LangChain, or similar) is a plus
• Strong communication skills and ability to work cross-functionally with engineering and product teams
• Experience working in Agile environments
• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Physics, or related quantitative field preferred

Virtual Requirements

To ensure a smooth and secure experience, please note the following:

• Cameras must be on during all virtual interviews.
• AI tools are not permitted to be used by the candidate during any part of the interview process.

Pay and Benefits

Targeted Pay Range: $83,000.00 - $138,200.00. This is part of a competitive total rewards package that could include other components such as: incentive, equity and benefits. Individual pay is determined by a number of factors including experience, location, internal pay equity, and other relevant business considerations. We review all teammate pay regularly to ensure competitive and equitable pay.

DICK'S Sporting Goods complies with all state paid leave requirements. We also offer a generous suite of benefits. To learn more, visit www.benefityourliferesources.com.