Senior Data Scientist, Product Analytics
About Rippling
Rippling is the first way for businesses to manage all of their HR & IT—payroll, benefits, computers, apps, and more—in one unified workforce platform.
By connecting every business system to one source of truth for employee data, businesses can automate all of the manual work they normally need to do to make employee changes. Take onboarding, for example. With Rippling, you can just click a button and set up a new employees' payroll, health insurance, work computer, and third-party apps—like Slack, Zoom, and Office 365—all within 90 seconds.
Based in San Francisco, CA, Rippling has raised $1.2B from the world's top investors—including Kleiner Perkins, Founders Fund, Sequoia, Greenoaks, and Bedrock—and was named one of America's best startup employers by Forbes.
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About the role
As the Senior Data Scientist for Product at Rippling, you will join a team of data scientists and analysts dedicated to boosting the relevance of all Rippling's product features and user flows.
As a senior player, your work will not only elevate the technical caliber of our PM and Eng teams with insights, but also partner to influence product GTM motions and feature roadmaps to fuel a powerful growth engine for all Rippling customers.
What you will do
Define, measure, and provide insights on key user flows across our portfolio of SKUs - e.g. platform, recruitment, credit cards, apps
Influence, work collaboratively and deeply embedded in sophisticated teams of product managers, engineers, and product GTM practitioners
Establish robust data assets and pipelines to collect, clean, and transform product data, ensuring integrity, accessibility for analysis and modeling, and scalability for new channels and geographies
Design, improve, and maintain business intelligence for our product teams
Develop and launch machine learning models that drive business impact (e.g. forecast customer behavior, spot highest-value actions, drive further engagement and retention)
Present data-driven insights and recommendations to influence executive decisions
Make a positive difference to our growth trajectory
What you will need
Track record of applying data science and analytics to solve product challenges
Knowledge of product analytic concepts, including user journeys, growth, drivers, engagement, retention
Proficiency with techniques and algorithms for experimentation, modeling, recommendation and decision systems
Fluency in SQL and Python
Familiarity with business intelligence best practices and tooling
Familiarity with data transformation best practices and tooling (e.g. incremental tables, metrics layer, dbt projects)
Exceptional communication, capable of collaborating effectively with both technical and non-technical audiences
Passion for nurturing a culture of data-driven decision-making and long-term impact within a fast-paced, ambiguous, hypergrowth environment
Additional Information
Rippling is an equal opportunity employer. We are committed to building a diverse and inclusive workforce and do not discriminate based on race, religion, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, age, sexual orientation, veteran or military status, or any other legally protected characteristics, Rippling is committed to providing reasonable accommodations for candidates with disabilities who need assistance during the hiring process. To request a reasonable accommodation, please email ********
Rippling highly values having employees working in-office to foster a collaborative work environment and company culture. For office-based employees (employees who live within a 40 mile radius of a Rippling office), Rippling considers working in the office, at least three days a week under current policy, to be an essential function of the employee's role.
This role will receive a competitive salary + benefits + equity. The salary for US-based employees will be aligned with one of the ranges below based on location; see which tier applies to your location here .
A variety of factors are considered when determining someone's compensation–including a candidate's professional background, experience, and location. Final offer amounts may vary from the amounts listed below.
The pay range for this role is:
129,000 - 225,750 USD per year (US Tier 1)
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