Data Scientist, Growth
New York City, NY | Seattle, WA; San Francisco, CA · 全职 · 市场与增长
需要对标的能力
大模型原理 · LLM 基础Agent · 智能体设计Agent 工程 · Harness / 脚手架AI Infra · 推理部署评测 · Eval 方法论多模态 · AI 生图AI 安全 · Prompt 注入防御AI 产品设计 · 产品化
岗位职责与要求
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.
About the role
As part of our growing Data Science and Analytics team, you will play an instrumental role in our company’s mission of building safe and beneficial artificial intelligence by driving data-informed decision making across our organization. You bring experience from high-bar teams and are eager to help shape the norms and best practices of a growing data science team as Anthropic continues to scale. In this unique company, technology, and moment in history, your work will be critical to informing our strategy as we deploy safe, frontier AI at scale to the world.
You’ll be the senior data science leader embedded in our Growth team and a strategic thought partner to its product and marketing leads. The Growth team’s job is to keep Anthropic on the exponential by getting more people and companies using and paying for Claude. You’ll help set direction across acquisition, activation, retention, and monetization: bringing a point of view on where to invest, how to grow revenue, and how to deliver more value for our users. As a tech lead manager, you’ll also manage a small team of Product Data Scientists, setting their agenda and raising the bar for how data shapes growth decisions.
Responsibilities:
• Act as a strategic thought partner to Growth product and marketing leads, helping shape growth strategy, roadmap priorities, and the major bets the team makes
• Set the data science agenda for Growth, deciding where the Product Data Science team can have the most impact and what it should deprioritize
• Manage and develop a small team of Product Data Scientists, coaching them to move from answering questions to shaping decisions
• Frame the most important and ambiguous questions facing Growth, from where the next users and companies will come from to what makes them stay and pay, size the opportunities, and make clear recommendations, including when they challenge the current direction
• Define how Growth measures success, establishing the core metrics, guardrails, and measurement frameworks that tie short-term wins to long-term value
• Set the standard for experimentation and causal inference across Growth, including holdouts and quasi-experimental methods where A/B tests aren’t practical, and personally lead the highest-stakes analyses
• Guide how Growth measures the return on its programs, including marketing incrementality, LTV, CAC, and payback, and turn the results into budget and channel recommendations
• Guide the team’s work on targeting and personalization, including how we decide which users get which message, offer, or experience and how we evaluate those decisions
• Turn complex analyses into clear narratives and recommendations that drive decisions with senior leadership and cross-functional partners
• Establish foundational data practices and shape the analytics infrastructure Growth needs to support rapid iteration and decision-making as our products grow
You may be a good fit if you:
• Have extensive experience in data science, including leading analytics for a growth or product area at significant scale
• Have 5+ years managing data science teams, including setting team direction and developing senior data scientists
• Have been a trusted partner to senior product, growth, or marketing leaders, with clear examples of changing a roadmap or high-stakes decision
• Bring strong product sense and business judgment across the growth funnel, including the ability to frame the right question and take a position with incomplete information
• Have deep expertise in experimental design, causal inference, and statistical modeling at high scale, with enough fluency in Python and SQL to stay hands-on and guide others’ technical work
• Communicate clearly in writing and in presentations, including to executive audiences
• Have a bias for action and thrive in ambiguous, fast-moving environments where you must create clarity and drive progress
• Care about the company’s mission of building helpful, honest, and harmless AI
Strong candidates may also have:
• Experience measuring marketing incrementality, including holdouts, geo experiments, or marketing mix modeling
• Experience with targeting, personalization, or uplift models in production
• Background at consumption-based, multi-product companies serving both consumers and enterprises
• Experience with AI/ML products or large language models, including using coding agents in your own analytical workflow
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:
$285,000—$380,000 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.
For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
查看中文参考译文
Anthropic 的使命是打造可靠、可解释、可引导的 AI 系统。我们希望 AI 对我们的用户和整个社会都是安全且有益的。我们的团队是一支快速成长的队伍,由专注的研究人员、工程师、政策专家和商业领袖组成,共同协作构建有益的 AI 系统。
关于该职位
作为我们不断壮大的 Data Science and Analytics 团队的一员,你将负责 Anthropic 营销投资背后的测量策略。这是一个基础性角色,从零开始构建 Anthropic 的营销测量体系。
你的首要关注点是付费媒体。我们正在将 marketing mix modeling 引入内部,你将构建并运营计量经济学工具包——包括 marketing mix modeling (MMM)、geo experiments、synthetic controls 和 incrementality testing——以告诉我们哪些营销投资真正推动了增长,并与我们的付费营销数据科学家紧密合作。在此基础上,你将把同样的因果严谨性扩展到 lifecycle 和其他营销项目:定义以激活和持续使用为导向的成功指标,并构建可自助服务的测量体系,使其规模超越任何单一嵌入式分析师。
主要职责
· 负责付费媒体的 incrementality measurement:构建并运营我们的内部 marketing mix model,并设计 geo experiments、synthetic-control studies 和 holdouts 来验证和校准它
· 将测量结果转化为预算和渠道建议,指导营销投资方向
· 为 lifecycle marketing 建立主要成功指标和 guardrails,以激活和活跃使用为锚点,而非触达
· 就营销干预措施提出假设,设计实验或因果推断研究,分析结果,并根据对关键指标的影响提出建议
· 通过建立指标、工具和最佳实践,使营销测量实现自助服务,让营销合作伙伴无需数据科学家参与即可回答常规问题
· 向技术性和非技术性受众呈现复杂的技术分析和建议
最低资格要求
· 具备营销 incrementality 方法的实操经验,包括 marketing mix modeling、geo experiments、synthetic controls 以及大规模的 A/B 或 holdout testing
· 精通因果推断和机器学习方法,并能判断何时适用每种方法
· 精通 Python 和 SQL
· 在 Marketing 或 Growth 环境中应用数据科学的经验
· 能够将复杂的分析转化为面向非技术受众的清晰建议
优先资格要求
· 7 年以上数据科学经验,其中大量时间嵌入 Marketing 或 Growth 团队
· 从零开始构建测量框架的经验,推动团队从描述性报告转向因果理解
· 有将复杂分析转化为高级营销利益相关者会采纳的建议的往绩
· 将 marketing mix modeling 引入内部的经验,或端到端运营而非通过供应商运营的经验
· 为产品驱动型业务定义 activation metrics 和 lifecycle measurement 的经验
· 在面向消费者和企业的按量计费、多产品公司的工作背景
· 在需求尚未明确时能够设定方向和做出决策
· 对 Anthropic 构建安全且有益的 AI 的使命感兴趣
对于销售岗位,提供的范围是该岗位的 On Target Earnings ("OTE") 范围,这意味着该范围包括销售佣金/销售奖金目标和该岗位的年基本工资。
年薪:
$285,000—$380,000 USD
后勤信息
最低学历要求:学士学位或同等的教育、培训和/或经验组合
所需专业领域:通过课程、培训或专业经验证明与该岗位相关的领域
最低经验年限:所需经验年限将与该职位的内部职级要求相对应
我们相信,最具影响力的 AI 研究将是大科学。在 Anthropic,我们作为一个统一的团队,仅专注于少数几个大规模研究项目。我们重视影响力——推进我们关于可引导、可信赖 AI 的长期目标——而非研究更小、更具体的课题。我们将 AI 研究视为一门实证科学,它与物理学和生物学的共同点,与传统计算机科学研究的共同点一样多。我们是一个极度协作的群体,经常举办研究讨论,以确保我们在任何时候都在追求最具影响力的工作。因此,我们非常重视沟通能力。
了解我们研究方向的最简单方式是阅读我们最近的研究。这项研究延续了我们团队在加入 Anthropic 之前的许多研究方向,包括:GPT-3、Circuit-Based Interpretability、Multimodal Neurons、Scaling Laws、AI & Compute、Concrete Problems in AI Safety 和 Learning from Human Preferences。
译文仅供辅助阅读,具体要求以原始招聘来源为准。