Data Scientist, Experimental Projects

• San Francisco, CA (Hybrid: 50% in office - Oyster Point)

Minimum requirements

• PhD with 3+ years, MS or MA with 6+ years, or BS or BA with 8+ years of data science or quantitative modeling experience.
• Proficiency in SQL and a computing language such as Python or R.
• Ability to effectively work both independently and with cross-disciplinary teams, including engineering and finance, to deliver impactful results.
• A demonstrated ability to manage and deliver on multiple projects with a high attention to detail.
• Solid business acumen and experience in synthesizing complex analyses into actionable recommendations.
• A track record of building relationships with and influencing the decisions of senior technical leadership.
• A builder's mindset with a willingness to question assumptions and conventional wisdom.
• Proficiency with artificial intelligence tools to accelerate model development, analysis, and coding.

• Strong knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and experimentation
• Experience deploying models in production and adjusting model thresholds to improve performance
• Experience designing, running, and analyzing complex experiments or using causal inference methods
• A builder’s mindset and willingness to question assumptions and conventional wisdom
• Experience working on ambiguous, zero-to-one problems and turning early evidence into practical decisions
• A strong bias for action, including the ability to identify the fastest credible way to test a hypothesis
• Comfort moving across different problem spaces and learning unfamiliar domains quickly
• Experience with distributed tools such as Spark or Hadoop
• A PhD or MS in a quantitative field, such as statistics, engineering, mathematics, economics, quantitative finance, science, or operations research