Senior Data Scientist

About the Role

dtcpay is building the infrastructure for the next generation of payments — where stablecoins, fiat, and digital assets coexist seamlessly. As our first Data Scientist, you will sit at the intersection of compliance, product, and commercial strategy, translating complex data into decisions that shape how we grow, operate, and stay ahead of risk.

Responsibilities

• This role begins with architecture before analysis. Before models can be built and insights can flow, the data foundation needs to exist — and building it is yours to own.
• Map and consolidate data across payment, compliance, and operations systems, establishing the pipelines, governance frameworks, and infrastructure that make reliable analytics possible at scale. This includes defining data classification standards, implementing PII detection and masking frameworks, and creating synthetic datasets that keep our analytical environment both powerful and compliant.
• Instrument user behaviour across merchant and consumer surfaces, build acquisition and retention models, and design the experimentation frameworks that give product teams confidence in the decisions they make. Your outputs here directly shape what gets built and in what order.
• Analyse transaction performance across channels, geographies, and merchant segments — identifying failure patterns, modelling optimal routing logic, and surfacing the signals that engineering and product teams need to improve conversion and reduce cost.
• Build the intelligence layer that moves our AML and transaction monitoring capabilities beyond static rule engines — developing risk scoring models, anomaly detection systems, and graph-based analytics that identify suspicious patterns at scale while remaining explainable and audit-ready.
• Own revenue forecasting, pricing analytics, and the data products that give leadership and regulators a clear view of how the business is performing and where it is headed.

Requirements

• 8+ years in data science or machine learning, preferably in fintech or financial services
• Proven experience building data infrastructure and pipelines from the ground up, not just consuming existing data
• Strong proficiency in Python and SQL; comfortable working across the full analytical stack
• Experience with anomaly detection, predictive modelling, graph analytics, or experimentation frameworks
• Able to work autonomously across multiple business domains and communicate findings clearly to non-technical stakeholders
• Familiarity with AML/CFT concepts, PDPA, or regulated environments is a strong plus