Senior Data Scientist

At Ripple, we’re building a world where value moves like information does today. It’s big, it’s bold, and we’re already doing it. Through our crypto solutions for financial institutions, businesses, governments and developers, we are improving the global financial system and creating greater economic fairness and opportunity for more people, in more places around the world. And we get to do the best work of our career and grow our skills surrounded by colleagues who have our backs.

If you’re ready to see your impact and unlock incredible career growth opportunities, join us, and build real world value.

Identify and collect key data to support data science research across Ripple. Develop and lead productanalytics initiatives for On-Demand Liquidity and Direct payment products, partnering closely with Product, Marketing, Business Development, and other business units. Build a deep understanding of the end-to-endfunctionality of RippleNet and end-to-end business activity driving product growth covering customertargeting, acquisition, and product usage. Define and supervise key product metrics, and design interactivedashboards using Tableau and other analytical tools.

Telecommuting permitted up to 50% per week within same geographic location as assigned office location.

40 hrs/week, Mon-Fri, 8:30 a.m. - 5:30 p.m.

MINIMUM REQUIREMENTS:

Must have a Bachelor's degree or foreign equivalent in Computer Science, Computer Engineering, Electrical Engineering or a related field, plus 5 years of experience in Data Science.

Alternatively, will accept Master's degree or foreign equivalent in Computer Science, Computer Engineering, Electrical Engineering or a related field plus 3 years of experience in Data Science.

Of the required experience, must have 3 years of experience in/with:

• SQL;
• Git.

Must have 2 years of experience in/with:

• Metrics definition and tracking;
• Statistical modeling (Python or R);
• BI tools including Tableau, Looker, or Mode; and
• Fintech or payments industries, including developing analytics pipelines for on-demand liquidity.

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