Senior Data Scientist, Search & Recommendations

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DICK'S Sporting Goods

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1948

🛒 Retail

⚽ Sports

🛍️ eCommerce

Retail • Sports • eCommerce

DICK'S Sporting Goods is the largest sporting goods retailer in the United States, offering a wide range of sporting equipment, apparel, and footwear. Committed to enriching communities through sports, DICK'S Sporting Goods also partners with major sports brands like UnderArmour, Patagonia, and Nike to provide high-quality products. The company is dedicated to inclusivity and sustainability, providing resources and support to help athletes and children participate in sports. Headquartered in Pittsburgh, DICK'S is at the forefront of innovative retail and fosters a people-first culture. The company also runs the DICK'S Sporting Goods Foundation, emphasizing the transformative power of sports.

📋 Description

• 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 • 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 to improve search and discovery experiences • Contribute to best practices in modeling, experimentation, and production ML systems

🎯 Requirements

• 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

🏖️ Benefits

• Health insurance • Paid time off • Retirement plans • Professional development opportunities • Generous suite of benefits