Data Scientist, Search Science (Ads)

Summit Health

1d • $83,300 - $166,800 • Hybrid

About The Position

As a Data Scientist on the Search Science team, you will focus on improving sponsored search capabilities to help grow ad revenue, a key business priority. Longer term, you will help evolve toward a unified ranking system that balances relevance, monetization, and customer retention. You will work alongside Senior Scientists and ML Engineers who will mentor you and help you grow. As a Data Scientist you will have an impact in the following areas: Sponsored Search Optimization: Help improve the relevance and ranking of sponsored products to increase ad revenue while maintaining a great customer experience. Analyze performance data and identify opportunities to improve sponsored product placement. Analytics & Opportunity Analysis: Conduct data analysis to identify areas for improvement across search and ads. Build dashboards, run exploratory analyses, and present insights to stakeholders to inform product and strategy decisions. Ranking & Relevance: Contribute to models that balance organic relevance with ad monetization. Help implement and test ranking improvements using established ML techniques. Personalization: Help integrate user signals (purchase history, preferences) into search to improve sponsored relevance for individual customers. Retrieval Systems: Support the development of retrieval systems that surface the right products, including work with both traditional (lexical) and newer (vector-based) approaches. Experimentation & Measurement: Help build evaluation pipelines and run A/B tests to measure the impact of model changes.

Requirements

• Degree in a STEM field (Computer Science, Statistics, etc.) with coursework or projects in machine learning
• 1–3 years of experience applying data science or machine learning to real-world problems (internships count)
• Strong coding skills in Python and SQL
• Familiarity with ML frameworks (PyTorch or TensorFlow) and their application to ranking, recommendations, or NLP
• Understanding of ranking concepts and experience with feature engineering
• Comfort working with large datasets and drawing actionable insights from data

Responsibilities

• Sponsored Search Optimization: Help improve the relevance and ranking of sponsored products to increase ad revenue while maintaining a great customer experience.
• Analyze performance data and identify opportunities to improve sponsored product placement.
• Analytics & Opportunity Analysis: Conduct data analysis to identify areas for improvement across search and ads.
• Build dashboards, run exploratory analyses, and present insights to stakeholders to inform product and strategy decisions.
• Ranking & Relevance: Contribute to models that balance organic relevance with ad monetization.
• Help implement and test ranking improvements using established ML techniques.
• Personalization: Help integrate user signals (purchase history, preferences) into search to improve sponsored relevance for individual customers.
• Retrieval Systems: Support the development of retrieval systems that surface the right products, including work with both traditional (lexical) and newer (vector-based) approaches.
• Experimentation & Measurement: Help build evaluation pipelines and run A/B tests to measure the impact of model changes.

Benefits

• Employees (and eligible family members) are covered by medical, dental, vision and more.
• Employees may enroll in our company’s 401k plan.
• Employees will also be eligible to receive discretionary vacation for exempt team members, paid holidays throughout the calendar year and paid sick leave.
• Other compensation includes eligibility for an annual bonus and the potential for restricted stock units based on role.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Number of Employees: 5,001-10,000 employees