Senior Product Data Scientist at Klaviyo

San Francisco, California, United States -

Full Time

Start Date

Immediate

Expiry Date

28 Apr, 26

Salary

213600.0

Posted On

28 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Product Development, Statistical Rigor, Product Intuition, R, Python, Causal Inference, Experimentation, A/B Testing, Multivariate Testing, Mixed Effects Models, Difference-in-Differences, Clustering Algorithms, Time Series Analysis, SQL, DBT

Industry

Marketing Services

Description

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 careers.klaviyo.com to see how we empower creators to own their own destiny. 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 SF 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 Massachusetts Applicants: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Our salary range reflects the cost of labor across various U.S. geographic markets. The range displayed below reflects the minimum and maximum target salaries for the position across all our US locations. The base salary offered for this position is determined by several factors, including the applicant’s job-related skills, relevant experience, education or training, and work location. In addition to base salary, our total compensation package may include participation in the company’s annual cash bonus plan, variable compensation (OTE) for sales and customer success roles, equity, sign-on payments, and a comprehensive range of health, welfare, and wellbeing benefits based on eligibility. Your recruiter can provide more details about the specific salary/OTE range for your preferred location during the hiring process. Base Pay Range For US Locations: $142,400—$213,600 USD Get to Know Klaviyo We’re Klaviyo (pronounced clay-vee-oh). We empower creators to own their destiny by making first-party data accessible and actionable like never before. We see limitless potential for the technology we’re developing to nurture personalized experiences in ecommerce and beyond. To reach our goals, we need our own crew of remarkable creators—ambitious and collaborative teammates who stay focused on our north star: delighting our customers. If you’re ready to do the best work of your career, where you’ll be welcomed as your whole self from day one and supported with generous benefits, we hope you’ll join us. AI fluency at Klaviyo includes responsible use of AI (including privacy, security, bias awareness, and human-in-the-loop). We provide accommodations as needed. By participating in Klaviyo’s interview process, you acknowledge that you have read, understood, and will adhere to our Guidelines for using AI in the Klaviyo interview Process. For more information about how we process your personal data, see our Job Applicant Privacy Notice. Klaviyo is committed to a policy of equal opportunity and non-discrimination. We do not discriminate on the basis of race, ethnicity, citizenship, national origin, color, religion or religious creed, age, sex (including pregnancy), gender identity, sexual orientation, physical or mental disability, veteran or active military status, marital status, criminal record, genetics, retaliation, sexual harassment or any other characteristic protected by applicable law. IMPORTANT NOTICE: Our company takes the security and privacy of job applicants very seriously. We will never ask for payment, bank details, or personal financial information as part of the application process. All our legitimate job postings can be found on our official career site. Please be cautious of job offers that come from non-company email addresses (@klaviyo.com), instant messaging platforms, or unsolicited calls. By clicking "Submit Application" you consent to Klaviyo processing your Personal Data in accordance with our Job Applicant Privacy Notice. If you do not wish for Klaviyo to process your Personal Data, please do not submit an application. You can find our Job Applicant Privacy Notice here and here (FR).

Responsibilities

Partner with product and engineering teams to identify and evaluate high-impact product opportunities using rigorous experimentation, causal inference, and predictive modeling. Define success metrics, build self-serve analytics tools, and communicate insights persuasively to stakeholders across the company.