Staff Data Scientist - Go to Market (GTM)
San Francisco, CA, USA
Posted on Wednesday, May 3, 2023
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 $700M from the world’s top investors—including Kleiner Perkins, Founders Fund, Sequoia, and Bedrock—and was named one of America’s best startup employers by Forbes (#12 out of 500).
About the role
Rippling’s Data Science team has led the effort in building the predictive analytics engine behind one of the fastest startup growth stories ever. We are rapidly launching new product lines and expanding globally, and it’s critical that our forecasting and growth strategy scale in line with this hypergrowth.
We’re looking for a Go-to-market Staff/Lead Data Scientist to join the central Data Science team. You’ll work in a cross-functional and fast-paced environment and your work will ensure we make the right decisions to fuel our growth, optimize our funnel and strengthen our unit economics. As an early data hire, you’ll have the opportunity to play a key role in advancing our modeling, influence the roadmap and tackle complex problems. We’re in the process of significantly increasing our Marketing spend, expanding our sales force alongside a drumbeat of new product launches.
What you will do
- Partner with cross-functional teams (Growth, Growth Engineering, Marketing Operations, Sales, FP&A and Data Engineering) to build out our data foundation for scale, define and standardize metrics, and promote cross-functional visibility into the supporting data and models.
- Develop and maintain forecasting models to predict key business metrics, such as ARR, user acquisition, and retention.
- Be the expert in experimental design, predictive modeling, and attribution.
- Proactively identify strategic opportunities and provide recommendations through ad-hoc and deep dive analysis.
- Develop and maintain high-visibility dashboards on forecasting, growth programs and their key performance metrics..
- Integrate additional data sources into our attribution models to provide additional insights on our various business growth levers.
What you will need
- Bachelor’s degree in Math, Analytics, Data Science, Economics, Statistics, Computer Science or other quantitative fields with 4+ years of industry experience or Master’s degree with 3+ years of experience.
- Strong proficiency in SQL, Tableau (or other Business Intelligence tools), and Python/ R (to perform analysis and create basic statistical models).
- Experience with causal inference and predictive modeling.
- Experience partnering closely in a SAAS setting with business partners from the Finance, Sales and Marketing teams.
- Ability to deliver actionable insights by synthesizing data into useful formats and conveying findings in a clear manner to influence decision makers.
- Ability to actively manage and influence stakeholders through strong communication skills, both in verbal and written form.
- Organized, attentive to detail, and intellectually curious.
- Ruthless prioritization and time management.
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.
Tier 1: $155,000 - $210,000/year
Tier 2: $139,000 - $189,000/year
Tier 3: $131,000 - $179,000/year
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 above.
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.
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