Data Scientist
We are currently partnering with a fast-growing, profitable digital assets platform that is expanding its global analytics capability. Operating with a lean, distributed team, the business supports millions of users worldwide through embedded financial technology solutions.
Our client is looking to hire a Data Scientist / Data Analyst to take ownership of the analytics function end-to-end. This is a high-impact role focused on designing tracking frameworks, building reporting infrastructure, leading experimentation initiatives, and delivering insights that directly influence product and commercial decisions.
This opportunity would suit someone who enjoys autonomy, thrives in fast-paced environments, and wants measurable influence over product direction and growth.
The Role
Product Analytics & Tracking
• Design and implement tracking across the full customer journey
• Enable week-on-week and month-on-month performance analysis across onboarding flows, transaction performance, and conversion metrics
• Define and monitor detailed conversion funnels, identifying friction points and optimisation opportunities
• Deliver structured reporting on behavioural trends, drop-offs, processing times, and platform efficiency
A/B Testing & Experimentation
• Evaluate and manage experimentation frameworks to support data-led product iteration
• Design statistically robust experiments, define KPIs, and analyse results to improve conversion and engagement
• Collaborate closely with Product and Engineering teams to prioritise testing initiatives and roadmap decisions
Dashboards & Data Engineering
• Build and maintain centralised analytics dashboards for operational and commercial reporting
• Develop reliable data pipelines to ensure accurate and timely reporting
Candidate Profile
Experience & Technical Skills
• 3+ years of experience in a Data Analyst or Data Scientist role
• Strong SQL capability with relational database experience preferred
• Proficiency in Python or R for statistical analysis and modelling
• Strong understanding of experimentation methodologies, including hypothesis testing and statistical significance
• Experience building dashboards using BI tools such as Looker, Tableau, Metabase, or Power BI
Competencies
• Strong product mindset with the ability to connect data insights to commercial outcomes
• Clear communicator who can present findings to both technical and non-technical stakeholders
• Self-sufficient, proactive, and comfortable identifying measurement gaps and opportunities
Desirable Experience
• Experience within digital assets, fintech, payments, or high-volume transaction environments
• Exposure to data warehousing, ETL processes, or event-driven systems
• Practical application of machine learning within production environments