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Data Scientist – Payments Risk Analytics

Data ScientistData ScientistFull TimeRemoteSeniorTeam 1,001-5,000Since 2017H1B No SponsorCompany SiteLinkedIn

Location

United States

Posted

14 days ago

Salary

0

Seniority

Senior

3 yrs expEnglishPandasPythonSQL

Job Description

Data Scientist – Payments Risk Analytics

Nuvei

• Analyze end-to-end ACH payment decisioning performance, including ML risk scores and risk rules, across approvals and losses. • Detect and analyze emerging trends in customer behavior, payment outcomes, and risk signals. • Evaluate how changes in strategies, data, or rules impact downstream decisioning and outcomes over time. • Independently define analytical questions, assemble datasets from multiple sources, and iterate toward insights without predefined reporting templates. • Use Python to perform exploratory data analysis, feature evaluation, cohort analysis, and experimentation across large ACH and risk datasets. • Develop repeatable analytical workflows and lightweight tooling in Python to accelerate insight generation and reduce manual analysis overhead. • Perform ad hoc analyses to evaluate the value and usefulness of new or existing data signals for risk decisioning. • Design analyses and reporting that support ongoing risk reviews, strategy discussions, and portfolio-level monitoring. • Explore and apply established and emerging analysis techniques to accelerate insight generation, trend detection, and decision support within regulated risk and payment datasets. • Partner with Risk, Product, and Relationship Management teams to inform strategy refinement and prioritization. • Communicate trends, findings, and recommendations clearly to internal stakeholders and, when applicable, external clients. • Work with large, imperfect, and regulated datasets to form actionable conclusions despite data gaps, latency, or attribution challenges.

Job Requirements

  • 3+ years of experience in payments risk, fraud analytics, or decisioning performance analysis within fintech, payments, or e-commerce.
  • Experience working with ACH or bank transfer payment data strongly preferred.
  • Strong SQL skills and experience working with large transactional datasets.
  • Strong Python skills for data analysis (e.g., pandas, notebooks), experimentation, and analytical automation.
  • Experience managing and analyzing data related to risk-based decision systems, or similar decisioning frameworks.
  • Ability to translate complex analytical findings into clear, actionable recommendations for technical and non-technical audiences.
  • Comfort operating in ambiguous environments with incomplete, delayed, or imperfect data.
  • Experience using AI-assisted tools or models for data analysis, pattern discovery, or insight generation is a plus.

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