Staff Data Scientist at Ripple – London | Jobyssey

You'll be the technical lead across Ripple's diverse product and business portfolio, defining the analytics vision and building the scientific frameworks the org uses to evaluate product and business performance. You'll use AI tooling to accelerate the speed and reach of analytics across the company. You'll partner with product and business leads to frame the most important questions, set the analytical bar, and ensure decisions rest on a consistent, thorough foundation. You'll operate as a force multiplier, solving the hardest problems, building frameworks others reuse, and levelling up data scientists across teams.

Responsibilities

Serve as the DS tech lead across multiple product and business teams, setting methodological standards and unblocking the hardest analytical problems across areas including Treasury, Markets, Custody, and XRPL
Partner with product and business leads to define analytics strategy, shaping which initiatives to invest in and what success looks like
Build scientific frameworks Ripple reuses at scale, including product and network health metrics, causal inference playbooks, liquidity and adoption models, and forecasting approaches
Pioneer AI-accelerated analytics by applying LLMs and agentic workflows to scale insight generation, automate routine analysis, and enable self-serve exploration for non-DS partners
Drive evidence-based evaluation of growth across customers, corridors, and on-chain activity, surfacing causal drivers behind adoption and volume
Define and communicate the metrics leadership runs on, translating complex results into clear narratives for executives and external stakeholders
Raise the bar for the DS function through thought leadership and mentorship across embedded teams

Requirements

8+ years in data science or quantitative analysis, with a track record of senior level impact across multiple teams
Demonstrated technical leadership across cross-functional teams, influencing roadmaps and strategy at both executive and execution levels
Proven experience designing reusable analytics and measurement frameworks that scale across products
Hands-on experience applying AI to accelerate analytics workflows (agentic analysis, AI-assisted insight generation, natural-language data interfaces)
Deep expertise in experimentation, causal inference, forecasting, and statistical modeling in a product environment
Expertise in Python or R, fluency in SQL, and experience with large-scale data tech (Databricks, Airflow, dBT a plus)
Experience with FinTech, payments, crypto, or blockchain data is a strong plus
Advanced degree (MS, PhD) in a quantitative field preferred
Exceptional communication skills

Benefits

Professional development budget
In-office collaboration flexibility (10+ days a month)
Bi-weekly all-company meeting with Leadership Team
Team offsites, team bonding activities, and happy hours
Competitive bonuses and equity
Competitive benefits covering physical and mental healthcare, retirement, family forming, and family support
Employee giving match
Mobile phone stipend
R&R days
Generous wellness reimbursement and weekly onsite & virtual programming
Generous vacation policy
Industry-leading parental leave policies and family planning benefits
Catered lunches, fully-stocked kitchens with premium snacks/beverages, and fun events

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