Data Scientist II

Rippling People Center Inc.•San Francisco, CA

29d

About The Position

We're looking for a Data Scientist to work in partnership with our Customer Experience teams to maximize customer retention, drive cross-sell across our product suite, and proactively reduce escalations & improve CSAT. As Rippling, you'll have the opportunity to dive into datasets to influence decision-making & impact strategy. If you are a self-starter who enjoys finding patterns and speaking through data, we're looking for someone like you!

Requirements

Master's degree in Analytics, Data Science, Economics, Statistics or a related field and at least 2~3 years of work experience, or equivalent.
Strong interest in actively working with Customer Success and Support teams, as well as cross-functional collaboration with Product & Marketing.
Strong proficiency in SQL, R/Python, Tableau, Mode, or other Business Intelligence tools.
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 senior stakeholders through strong business communication skills, both verbal and written.
Ruthless prioritization and time management.
Organized, attentive to detail, and intellectually curious.

Nice To Haves

Bonus points for experience with B2B SaaS companies, Salesforce CRM & Service Cloud, as well as executive-level exposure.

Responsibilities

Use quantitative analysis and the presentation of data to share beyond the numbers and understand what drives our business.
Build full-cycle analysis using SQL, R, Python, or other scripting and statistical tools.
Produce recommendations and use statistical techniques and hypothesis testing to validate your findings.
Provide insights to help business leaders understand marketplace dynamics, user behaviors, and long-term trends.
Identify and measure levers to help move essential metrics and make recommendations.
Report against our goals by identifying essential metrics and building executive-facing dashboards to track progress.
Collaborate with data engineering to implement, document, validate, and monitor our evolving data infrastructure.
Work autonomously as an individual contributor as well as showcase horizontal leadership, driving initiatives to completion and proactively identifying opportunities that will move the needle in the long run.

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