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Data Scientist, Safeguards

External
Anthropic logoAnthropic · New York City, NY
$275K–$370K/yrFull-timeOn-site2w ago
PythonSAFeSQL
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About the role

As an early member of our Safeguards Data Science and Analytics team, you will play an instrumental role in our company's mission of building safe and beneficial artificial intelligence by building and scaling a data driven culture from the ground up. In this unique company, technology, and moment in history, your work will be critical to informing our product and commercial strategy as we deploy safe, frontier AI at scale to the world. You will work closely with product, engineering, policy & enforcement to define and measure key company success metrics, analyze user behavior to identify new enforcement opportunities and build a culture of developing and testing hypotheses through experimentation. You've worked in cultures of excellence in the past, and are eager to apply that experience to building robust and scalable systems and processes as our company goes through a phase of rapid growth.

Responsibilities

  • Deep dive into user behavior data to provide insights on safety concerns
  • Define core metrics that measure the team's success. Set goals, build forecasts, monitor performance, and develop actionable reporting
  • Identify and size opportunities to improve the product, influencing product roadmap through your insights and recommendations
  • Develop hypotheses on product changes, design controlled experiments, analyze the results, and make recommendations based on impact to key metrics
  • Build a data driven culture from the ground up by establishing foundational data best practices and making data more accessible across the company

Requirements

  • Expertise in Python, SQL, and data visualization tools.
  • A bias for action and urgency, not letting perfect be the enemy of the effective.
  • A strong disposition to thrive in ambiguity, taking initiative to create clarity and forward progress.
  • A deep curiosity and energy for pulling the thread on hard questions.
  • Experience in turning open questions and data into concise and insightful analysis.
  • Highly effective written communication and presentation skills.
  • A passion for the company's mission of building helpful, honest, and harmless AI.
  • 6+ years of experience in data science or analytics roles, preferably in an infrastructure or operations context.
  • 3+ years of experience deeply embedding in Product teams.
  • Experience working on safety, anti-abuse, integrity shaped problems.
  • Deadline to apply: None. Applications will be reviewed on a rolling basis.
  • The annual compensation range for this role is listed below.
  • For sales roles, the range provided is the role's On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
  • Annual Salary:
  • $275,000 - $370,000 USD
  • Logistics
  • Minimum education: Bachelor's degree or an equivalent combination of education, training, and/or experience
  • Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
  • Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
  • Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
  • Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

Benefits

Performance bonus

Additional Information

About Anthropic Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.


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