Senior Product Data Scientist

<div class="content-intro"><p><em>At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day. We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements. If you’re a close but not exact match with the description, we hope you’ll still consider applying. Want to learn more about life at Klaviyo? Visit <a class="_ymio1r31 _ypr0glyw _zcxs1o36 _mizu194a _1ah3dkaa _ra3xnqa1 _128mdkaa _1cvmnqa1 _4davt94y _4bfu18uv _1hms8stv _ajmmnqa1 _vchhusvi _kqswh2mm _ect4ttxp _syaz13af _1a3b18uv _4fpr8stv _5goinqa1 _f8pj13af _9oik18uv _1bnxglyw _jf4cnqa1 _30l313af _1nrm18uv _c2waglyw _1iohnqa1 _9h8h12zz _10531ra0 _1ien1ra0 _n0fx1ra0 _1vhv17z1" href="http://klaviyo.com/careers" data-renderer-mark="true">klaviyo.com/careers</a> to see how we empower creators to own their own destiny.</em></p></div><p>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. <strong>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. </strong></p> <h3><strong>What You’ll Do:</strong></h3> <ul> <li>Partner with product and engineering teams to identify and evaluate high-impact product opportunities through rigorous experimentation, causal inference, and predictive modeling</li> <li>Lead the design, implementation, and analysis of experiments — including A/B tests and multivariate tests — ensuring sufficient power, correct statistical methods, and actionable recommendations</li> <li>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.</li> <li>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.</li> <li>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.</li> <li>Communicate insights clearly and persuasively to cross-functional stakeholders, from product teams to executive leadership</li> </ul> <h3><strong>Who You Are</strong></h3> <ul> <li>You have 7+ years of experience in data science, product analytics, or applied statistics, preferably in a B2B SaaS or product-focused environment</li> <li>You hold a degree in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, or Engineering</li> <li>You are highly proficient in SQL and either Python or R, and comfortable using DBT for analytics engineering</li> <li>You have deep expertise in experimentation and statistical analyses.</li> <li>You bring strong business intuition and the ability to translate ambiguous questions into clear analytical plans</li> <li>You work with speed and focus, balancing analytical rigor with the urgency and iteration cadence of product development</li> <li>You are a compelling communicator who can frame complex statistical findings into product-relevant insights</li> <li>You thrive in cross-functional settings and are energized by using data to drive product decisions that improve customer outcomes</li> </ul> <h3 ... (truncated, view full listing at source)