Data Scientist (Fintech / Onchain Analytics)
PulseRise Technologies
About the role
About
We are looking for an experienced Data Scientist to drive data‑informed decision‑making across product, finance, and engineering within a fast‑growing crypto payments infrastructure company. This role sits at the intersection of on‑chain analytics, product experimentation, and business performance optimization. You will transform transaction flows, routing behavior, and user journey data into insights that directly shape roadmap and growth strategy. The position requires strong statistical expertise, hands‑on experimentation experience, and comfort working with large‑scale financial datasets. You will collaborate closely with product leaders and the CFO to evaluate unit economics, conversion funnels, and market dynamics. This is a high‑ownership role based in New York City, working in‑person with the core team.
Details
- Location: NYC
- Work Model: Hybrid (4 days in‑office)
- Employment Type: Full‑time
- Industry: Fintech / Crypto Infrastructure
- Start Date: ASAP
Key Responsibilities
- Design scalable data models to analyze transaction flows, routing behavior, and user journeys
- Build and maintain reliable data pipelines and transformations ensuring data quality and reproducibility
- Partner with CFO and leadership to analyze unit economics, revenue drivers, and growth performance
- Define and track product KPIs such as conversion, retention, engagement, and cohort performance
- Design and execute experiments (A/B testing, causal inference, uplift modeling)
- Translate complex quantitative findings into clear, actionable insights for technical and non‑technical stakeholders
- Analyze market behavior and liquidity patterns within crypto or DeFi ecosystems
- Support roadmap decisions with production‑grade data insights
Requirements
- 5+ years of experience using Python and SQL in data science or analytics roles
- Strong background in statistics, experimentation design, and causal inference
- Experience analyzing user behavior, funnels, retention, and product performance
- Experience working with modern data platforms (Redshift, Snowflake, Databricks)
- Experience with data transformation/orchestration tools such as dbt
- Strong communication skills and ability to explain complex analysis clearly
- Experience working in cross‑functional environments
Nice to Have
- Experience analyzing large‑scale transaction or financial datasets (payments, trading, lending)
- Experience with ML libraries (Pandas, NumPy, scikit‑learn; PyTorch or TensorFlow a plus)
- Familiarity with spreads, slippage, liquidity dynamics in crypto markets
- Background in fintech, crypto analytics, or DeFi protocols
- Deep interest in Web3 infrastructure and on‑chain ecosystems
Employment Type: FULL_TIME
Requirements
- 5+ years of experience using Python and SQL in data science or analytics roles
- Strong background in statistics, experimentation design, and causal inference
- Experience analyzing user behavior, funnels, retention, and product performance
- Experience working with modern data platforms (Redshift, Snowflake, Databricks)
- Experience with data transformation/orchestration tools such as dbt
- Strong communication skills and ability to explain complex analysis clearly
- Experience working in cross-functional environments
Responsibilities
- Design scalable data models to analyze transaction flows, routing behavior, and user journeys
- Build and maintain reliable data pipelines and transformations ensuring data quality and reproducibility
- Partner with CFO and leadership to analyze unit economics, revenue drivers, and growth performance
- Define and track product KPIs such as conversion, retention, engagement, and cohort performance
- Design and execute experiments (A/B testing, causal inference, uplift modeling)
- Translate complex quantitative findings into clear, actionable insights for technical and non-technical stakeholders
- Analyze market behavior and liquidity patterns within crypto or DeFi ecosystems
- Support roadmap decisions with production-grade data insights
Skills
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