Senior Product Data Scientist

Klaviyo • Boston, MA

16h • Hybrid

About The Position

We’re looking for someone who thrives at the intersection of data science and product development, someone who pairs deep statistical rigor with product intuition, and can fluidly move between building complex models in R or Python and advising product leaders and executives on strategic decisions. You should be just as comfortable designing and validating a causal inference framework as you are communicating its implications to stakeholders across the company. Please note that this is a hybrid role that requires 3 days/week in our Boston office. Fully remote candidates will not be considered at this time. What You’ll Do: Partner with product and engineering teams to identify and evaluate high-impact product opportunities through rigorous experimentation, causal inference, and predictive modeling Lead the design, implementation, and analysis of experiments — including A/B tests and multivariate tests — ensuring sufficient power, correct statistical methods, and actionable recommendations Conduct statistical research projects to uncover patterns in customer behavior, evaluate product performance, and identify causal relationships — using methods such as Mixed Effects Models, Difference-in-Differences, clustering algorithms, and time series analysis to guide product strategy and decision-making. Define the right product and customer metrics to measure success, and build scalable, self-serve analytics tools and dashboards that enable product managers and cross-functional stakeholders to make data-informed decisions independently. Collaborate with data engineering to define and implement reliable data pipelines and DBT models that ensure clean, well-structured, and trustworthy data for downstream analysis and self-serve use. Communicate insights clearly and persuasively to cross-functional stakeholders, from product teams to executive leadership Who You Are You have 7+ years of experience in data science, product analytics, or applied statistics, preferably in a B2B SaaS or product-focused environment You hold a degree in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, or Engineering You are highly proficient in SQL and either Python or R, and comfortable using DBT for analytics engineering You have deep expertise in experimentation and statistical analyses. You bring strong business intuition and the ability to translate ambiguous questions into clear analytical plans You work with speed and focus, balancing analytical rigor with the urgency and iteration cadence of product development You are a compelling communicator who can frame complex statistical findings into product-relevant insights You thrive in cross-functional settings and are energized by using data to drive product decisions that improve customer outcomes Why You’ll Love This Role Influence the direction of a high-impact product area and help define how success is measured Work alongside a world-class data team where experimentation and modeling are first-class tools Join a company where data science is embedded in the product development lifecycle, not siloed as reporting support Be part of a culture that values intellectual rigor, collaborative problem-solving, and continuous learning We use Covey as part of our hiring and / or promotional process. For jobs or candidates in NYC, certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on April 3, 2025. Please see the independent bias audit report covering our use of Covey here

Requirements

• You have 7+ years of experience in data science, product analytics, or applied statistics, preferably in a B2B SaaS or product-focused environment
• You hold a degree in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, or Engineering
• You are highly proficient in SQL and either Python or R, and comfortable using DBT for analytics engineering
• You have deep expertise in experimentation and statistical analyses.
• You bring strong business intuition and the ability to translate ambiguous questions into clear analytical plans
• You work with speed and focus, balancing analytical rigor with the urgency and iteration cadence of product development
• You are a compelling communicator who can frame complex statistical findings into product-relevant insights
• You thrive in cross-functional settings and are energized by using data to drive product decisions that improve customer outcomes

Responsibilities

• Partner with product and engineering teams to identify and evaluate high-impact product opportunities through rigorous experimentation, causal inference, and predictive modeling
• Lead the design, implementation, and analysis of experiments — including A/B tests and multivariate tests — ensuring sufficient power, correct statistical methods, and actionable recommendations
• Conduct statistical research projects to uncover patterns in customer behavior, evaluate product performance, and identify causal relationships — using methods such as Mixed Effects Models, Difference-in-Differences, clustering algorithms, and time series analysis to guide product strategy and decision-making.
• Define the right product and customer metrics to measure success, and build scalable, self-serve analytics tools and dashboards that enable product managers and cross-functional stakeholders to make data-informed decisions independently.
• Collaborate with data engineering to define and implement reliable data pipelines and DBT models that ensure clean, well-structured, and trustworthy data for downstream analysis and self-serve use.
• Communicate insights clearly and persuasively to cross-functional stakeholders, from product teams to executive leadership

Benefits

• Influence the direction of a high-impact product area and help define how success is measured
• Work alongside a world-class data team where experimentation and modeling are first-class tools
• Join a company where data science is embedded in the product development lifecycle, not siloed as reporting support
• Be part of a culture that values intellectual rigor, collaborative problem-solving, and continuous learning

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 501-1,000 employees