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Staff Data Scientist, Ranking (Remote - US) at Jobgether. This position is posted by Jobgether on behalf of a partner company. We are currently looking for a . Staff Data Scientist, Ranking. in . United States. .. As a Staff Data Scientist on the Ranking team, you will lead efforts to improve how users are connected with the best possible recommendations through advanced data science and machine learning techniques. You will design and implement evaluation frameworks, analyze system performance, and identify signals to enhance search, ranking, and personalization. Collaborating closely with engineering, product, and clinical teams, you will translate research insights into actionable improvements that directly impact user experience. This role combines scientific rigor with practical application to solve meaningful problems, helping individuals access high-quality, personalized services efficiently. You will operate in a highly collaborative, mission-driven environment, influencing both strategy and execution across large-scale systems.. . Accountabilities. Analyze and evaluate the performance of search and ranking systems using both offline and online metrics.. Develop frameworks to measure relevance, conversion, and long-term outcomes.. Conduct exploratory research to identify new ranking signals and personalization opportunities.. Collaborate with ML engineers to implement research findings into production-ready models and features.. Partner with product, clinical, and engineering teams to define success metrics and guide experimentation.. Communicate findings, recommendations, and business implications effectively to technical and non-technical stakeholders.. PhD or Master’s degree in Statistics, Computer Science, or a related quantitative field.. 9+ years of experience in data science, applied machine learning, or a related field.. Strong proficiency in Python, SQL, and experimentation/causal inference techniques.. Experience with ranking, search, or recommendation systems (e.g., relevance modeling, click modeling, LTR methods).. Ability to handle ambiguous, open-ended research questions and translate findings into actionable insights.. Excellent communication skills for conveying complex ideas clearly and building trust across teams.. Passion for improving access to personalized healthcare and advancing outcomes for users.. Nice to Have:. Experience with large-scale search or recommendation evaluation frameworks (e.g., NDCG, MAP, offline/online A/B testing).. Familiarity with fairness or bias evaluation in machine learning systems.. . Company Location: United States.