Staff Data Scientist

Full-time | On-site

Location: San Francisco

We are a well-funded, rapidly growing technology company building advanced AI solutions for the enterprise. We are seeking a Staff Data Scientist to bring deep technical rigor, statistical expertise, and product acumen to our data-driven decision-making process. This high-impact role requires an ability to structure ambiguous problems and directly influence product strategy and company performance.

As a Staff Data Scientist, you will be the primary driver of experimentation culture and advanced analysis, ensuring data is used strategically to measure growth, test product changes, and evaluate the performance of our AI models.

In this role, you will:

• Conduct deep-dive analyses using advanced statistical methods on user behavior, product performance, and business outcomes to surface actionable insights for executive leadership.
• Design, implement, and analyze controlled A/B test experiments at scale to rigorously measure the impact of product changes and customer experience initiatives.
• Enhance and extend our data models, metrics, and dashboards to ensure consistent, scalable reporting across all teams.
• Evaluate and interpret the performance of Machine Learning (ML) models (including classification, recommendation, and LLM-based systems), helping product and engineering teams reason through trade-offs and business implications.
• Collaborate with Product and Engineering to embed experimentation and measurement best practices into the entire product development lifecycle.
• Communicate findings clearly and persuasively to executives and cross-functional stakeholders, translating complex analysis into strategic direction.
• Build and continuously improve the data stack, ensuring models, pipelines, and tools empower efficient self-serve analytics across the company.

This position requires a seasoned data professional with a strong foundation in statistics, experimental design, and the ability to drive business impact through data.

• 5+ years (or equivalent experience) in data science or product analytics roles, ideally within high-scale consumer or marketplace products.
• Advanced proficiency in SQL and Python, with a solid foundation in statistics and experimental design.
• Proven track record of designing, running, and analyzing experiments at scale, and establishing an experimentation culture.
• Strong ability to structure ambiguous problems and translate them into rigorous analytical approaches.
• Ability to reason about and analyze machine learning models, understanding their assumptions, trade-offs, and impact on product and customer outcomes.
• Excellent communication skills, with demonstrable experience influencing strategic decision-making across diverse teams.

Work Policy:

• This is a full-time, on-site role based in San Francisco, requiring 5 days per week in the office.
• Visa sponsorship is not available.

Join a team backed by top-tier investors and poised for massive growth, where your analytical work will directly influence the company's trajectory.

• Salary Range: $200,000 - $300,000 (Base Salary).
• Equity: Competitive Equity offering, reflecting the senior and high-impact nature of the role.
• Strategic Influence: Opportunity to influence at the highest level by shaping product strategy and establishing company-wide measurement practices.

Due to the high volume of applications we anticipate, we regret that we are unable to provide individual feedback to all candidates. If you do not hear back from us within 4 weeks of your application, please assume that you have not been successful on this occasion. We genuinely appreciate your interest and wish you the best in your job search.

Commitment to Equality and Accessibility:

At MLabs, we are committed to offer equal opportunities to all candidates. We ensure no discrimination, accessible job adverts, and providing information in accessible formats. Our goal is to foster a diverse, inclusive workplace with equal opportunities for all. If you need any reasonable adjustments during any part of the hiring process or you would like to see the job-advert in an accessible format please let us know at the earliest opportunity by emailing human-

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