Role in brief
RiskPod, a Web3 payments company, seeks a Data Scientist for Product Analytics. This role involves designing data models, defining metrics, and running experiments to guide product development and user experience. Candidates with strong Python, SQL, and statistical skills, particularly in experimentation and causal inference, should apply to help shape the product roadmap.
About the role
This role focuses on product analytics within a Web3 payments environment. The work involves creating data models to understand transaction flows, routing, and user paths. A key part of the job is to establish and monitor important product and business metrics like conversion rates, user retention, engagement levels, and unit economics.
The position operates at the intersection of product, engineering, and finance. It requires transforming data from both on-chain activities and product usage into actionable insights. These insights directly influence the company's product roadmap, user experience design, and overall business performance, ensuring that product development is data-driven.
Success in this role means influencing product decisions through rigorous experimentation and analysis. This includes designing and executing A/B tests and other forms of statistical and causal inference. The ability to communicate complex analytical findings clearly to both technical and non-technical audiences, including leadership, is essential for driving strategic outcomes.
The salary for this position ranges from $150,000 to $180,000 USD.
Skills that matter here
- Python: This role requires using Python for data science and analytics tasks, indicating its importance for data manipulation and model building.
- SQL: SQL is necessary for querying and managing data, forming the basis for analytical work.
- statistics: A strong foundation in statistics is needed to interpret data, design experiments, and draw valid conclusions.
- experimentation design: This skill is crucial for setting up controlled tests, such as A/B tests, to evaluate product changes.
- causal inference: Causal inference techniques are applied to understand the true impact of product interventions and business decisions.
Who this role suits
- A candidate with at least five years of experience in data science or analytics.
- Someone who can translate complex data into clear, actionable advice for different audiences.
- An individual comfortable working at the intersection of product development, engineering, and financial analysis.
- A person who values using data and experimentation to guide strategic product decisions.
From the employer
- Design and build scalable data models to analyze transaction flows, routing behavior, and end-to-end user journeys.
- Define, track, and interpret key product and business metrics (conversion, retention, engagement, unit economics).
- Run experiments (A/B tests and beyond), apply statistical and causal inference, and influence product decisions.
- Translate complex analyses into clear, actionable insights for technical and non-technical stakeholders, including leadership.
- 5+ years of experience using Python and SQL in data science, analytics, or related roles.
- Strong foundation in statistics, experimentation design, and causal inference (A/B testing, uplift analysis, quasi-experiments).
Questions about this role
What is the remote work policy for this position?
This is a fully remote position, but candidates should be located in New York.
What skills are required for this role?
Required skills include Python, SQL, statistics, experimentation design, and causal inference, with specific mention of Pandas, NumPy, scikit-learn, PyTorch, and TensorFlow in the stack.
What is the salary range for this position?
The salary range for this role is between $150,000 and $180,000 USD.
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