Senior Data Scientist, Product Analytics

Position Overview

Lightspark is building open payments for the Internet—always-on payment solutions powered by Bitcoin, the only open, neutral network for moving value. With enterprise tools like Connect, UMA, and Spark, businesses can send and receive money instantly, securely, and at a fraction of the cost. Headquartered in Los Angeles, California and serving the world, Lightspark is on a mission to reinvent the payment landscape.

Role: Senior Data Scientist – You will drive data-informed decisions across Product, Finance, Compliance, and Strategy by bridging our data infrastructure with the business teams that rely on actionable insights.

Key Responsibilities

• Own Key Metrics & Measurement: Design and implement measurement frameworks for core products (UMA, Spark, Lightspark Payments); define success metrics for strategic partners like Nubank and SoFi; build dashboards and reporting tools to enable self-service analytics; track product health, user engagement, retention, and transaction patterns.
• Enable Cross-Functional Decision-Making: Partner with Finance on pricing analysis, margin optimization, and revenue forecasting; support Compliance with transaction monitoring rules, KYC/AML thresholds, and risk scoring frameworks; work with Product teams to prioritize features based on data-driven insights; provide strategic analysis for go-to-market decisions and partnership evaluations.
• Build Data Products & Pipelines: Extend the data infrastructure to support new analytics use cases; build domain-specific data models and pipelines using dbt, SQL, and Python; create scalable, maintainable analytics code; collaborate with Data Engineers to design efficient data architectures.
• Drive Data Culture: Advocate for data-driven decision-making across the organization; train teams on using data tools and interpreting metrics; identify and resolve gaps in the data ecosystem; balance speed with quality to ship fast and iterate based on feedback.

Required Qualifications

• 5+ years of experience in data science or related roles
• Expert-level SQL skills with the ability to write complex queries and design efficient data models
• Strong Python programming skills to build pipelines and automate analyses
• Proven ability to define metrics and measurement frameworks from scratch
• Track record of influencing product and business decisions with data
• Strong communication skills for explaining technical concepts to non-technical stakeholders
• Self-starter mentality with the ability to work independently and unblock challenges
• Understanding of statistical concepts including A/B testing, causal inference, and experimentation

Preferred Qualifications

• Experience with modern data tools such as DBT, Airflow/Dagster, BigQuery/Snowflake/Databricks, and Looker/Mode/Hex
• Experience in payments, fintech, or crypto/blockchain companies
• Familiarity with compliance, fraud detection, or risk analytics
• Background in both startups and larger tech companies
• Experience with product analytics tools like Amplitude, Mixpanel, or Segment
• Educational background in quantitative fields (Computer Science, Engineering, Math, Statistics, or Economics)