Staff Data Scientist, Ranking (Remote - US)

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.

Requirements

• 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.

Benefits

• Competitive base salary ($215,900–$254,000) with performance-based variable compensation and equity grants.
• Health, dental, and vision coverage, including HSA/FSA options.
• Retirement savings plan (401K) and financial wellness support.
• Remote work options with flexibility, plus offices in select locations.
• Work-from-home stipend, therapy reimbursement, and wellness support programs.
• Paid parental leave (16 weeks for eligible employees).
• Generous PTO, 13 paid holidays, and a Holiday Break between December 25–31.
• Professional development, training, and continuous learning opportunities.
• Inclusive and diverse culture committed to equitable access and representation.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.
🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.
📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.
🎯 Based on this analysis, we automatically shortlist the three candidates with the highest match to the role.
🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.

Thank you for your interest!