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Salary: USD 223,000 - 358,800 / annual
Squarespace is seeking a Senior Manager of Data Science and Machine Learning to lead a team of 12 data scientists and ML engineers in New York. Reporting to the VP of Data, you will set the technical and strategic direction for predictive modeling, causal inference, and AI evaluation systems that directly inform customer acquisition, retention, and engagement at scale.
In this hybrid role (3 days per week in the NYC office), you will lead and develop a team of 12, including three direct reports who manage their own teams. You'll work closely with product, engineering, and analytics partners to introduce new data-driven capabilities across Squarespace's products and decision systems. Key responsibilities include:
- Setting technical and strategic direction for predictive modeling, causal inference, and AI evaluation across product and business priorities
- Applying data science to major growth levers: marketing measurement, sales growth, product optimization, customer support allocation, and risk/credit modeling
- Partnering with product, engineering, and business leaders to translate complex statistical and ML work into actionable decisions and systems
- Building systems, processes, and team culture that improve the quality and speed of data science delivery
- Evolving ML infrastructure and tooling as AI capabilities grow at Squarespace
- Developing senior individual contributors and team leads simultaneously
Squarespace is a design-driven platform empowering millions of entrepreneurs to build brands and businesses online. The company operates globally with offices in New York, Dublin, and Aveiro, and offers a comprehensive benefits package including flexible PTO, 12 weeks paid parental leave, education reimbursement, and stock options.
Requirements:
- 12+ years in data science or machine learning, including experience leading technical teams through complex, high-stakes projects
- 5+ years managing managers, with demonstrated ability to develop senior individual contributors and team leads simultaneously
- Hands-on experience building or overseeing production predictive models, causal inference frameworks, or AI evaluation systems
- Skill at aligning product, engineering, and business partners around a shared roadmap and navigating trade-offs clearly, especially in explaining statistical or technical trade-offs to executives
- Experience scaling a data science or ML function, including team structure, hiring, and technical standards
Nice to Have:
- Experience building or overseeing LLM evaluation harnesses, including golden sets and LLM-as-judge methods
- Familiarity with prompt and model lifecycle management in production
- Experience designing human-in-the-loop review for AI-driven features
- Background in marketing science, experimentation, or credit/risk modeling
