RippleX is a division at Ripple focused on accelerating adoption of the digital asset XRP and the XRP Ledger in blockchain projects across i...
RippleX is a division at Ripple focused on accelerating adoption of the digital asset XRP and the XRP Ledger in blockchain projects across industries and technologies. RippleX aims to build a robust ecosystem of third-party developers, projects and companies that build, grow and monetize their applications on XRP, and other blockchain technologies.
As a data scientist within the Product Insights team, you will leverage data and statistical methods to help RippleX solve impactful product, marketing, and growth problems such as funnel analysis, attribution modeling, causal inference, user incentives, and more.
This role will partner closely with Product, Marketing, Design, Engineering and other teams to drive cross-functional data science projects from beginning to end. Our team gives you full ownership over the projects you tackle, so you should be a person who is bold and dreams big, then executes well.
What You'll Do
What We Are Looking For
- Use quantitative analysis to understand user intent, behavior, and product trends, and present methodology and key insights to stakeholders and senior leaders.
- Build and maintain full-cycle experiments, reports, and dashboards using Python/R, SQL, and other scripting and statistical tools.
- Produce designs and recommendations for growth strategies such as user incentives and use statistical techniques to measure results.
- Report against our goals, design essential business and product metrics, and build executive-facing dashboards.
- Develop and implement modeling and testing frameworks to ensure that we operate with the highest level of scientific rigor.
What We Offer
- A degree in Math, Physics, Statistics, Economics, Computer Science, or similar domain
- 2-5 years in an Analytics/Data Science type role. Experience working with funnels, cohort analyses, time series analyses, regression models a plus.
- Expertise of SQL queries, ETL, A/B Testing, and statistical analysis (e.g. hypothesis testing, experimentation, regressions) with statistical packages, such as Python or R.
- Hands-on experience building dashboards with a data visualization tool such as Tableau, Looker, Data Studio, etc.
- Ability to take ambiguous problems and solve them in a structured, hypothesis-driven, scientific way.
- Passion to initiate and lead projects to completion in a fast paced, ever changing, start-up environment.
Who We Are
- The chance to work in a fast-paced startup environment with experienced industry leaders
- A learning environment where you can dive deep into the latest technologies and make an impact
- Competitive salary and equity
- 100% paid medical and dental and 95% paid vision insurance for employees starting on your first day
- 401k (with match), commuter benefits
- Industry-leading parental leave policies
- Generous wellness reimbursement and weekly onsite programs
- Flexible vacation policy - work with your manager to take time off when you need it
- Employee giving match
- Modern office in San Francisco's Financial District
- Fully-stocked kitchen with organic snacks, beverages, and coffee drinks
- Weekly company meeting - ask me anything style discussion with our Leadership Team
- Team outings to sports games, happy hours, game nights and more!
Ripple is doing for value what the internet did for information: enabling its instant and seamless flow around the world. We call this the Internet of Value (IoV). Using blockchain and cryptocurrency technology, Ripple is dedicated to creating powerful gains in financial efficiency, equity and inclusion. In addition, Ripple is developing and enabling the future use cases that will catalyze the new digital economy for governments, businesses and consumers.
Ripple has offices in San Francisco (HQ), New York, London, Mumbai, Singapore, São Paulo, Reykjavík, Washington D.C. and Dubai.Ripple is an Equal Opportunity Employer. We're committed to building a diverse and inclusive team. We do not discriminate against qualified employees or applicants because of race, color, religion, gender identity, sex, sexual preference, sexual identity, pregnancy, national origin, ancestry, citizenship, age, marital status, physical disability, mental disability, medical condition, military status, or any other characteristic protected by local law or ordinance.
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