Data Scientist – Payments Risk Analytics

Nuvei

Data Scientist at Nuvei analyzing ACH payment transactions and risk signals. Collaborating with Risk teams to optimize payment performance through data insights.

Posted 5/14/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

PandasPythonSQL

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

🌐 Worldwide ❌ Jobs You've Hidden ⭐️ Saved Jobs ✅ Applied Jobs ✉️ Email Alerts 👤 Account Nuvei Website LinkedIn All Job Openings 1001 - 5000 employees Founded 2017 💳 Fintech 🛍️ eCommerce 🎮 Gaming 💰 $500M Post-IPO Secondary on 2021-05 Fintech
eCommerce
Gaming Nuvei is a payment technology company specializing in providing seamless and innovative payment solutions for businesses across various industries. It offers a range of services including pay-ins, payouts, global acquiring, bank transfers, real-time payments, and alternative payment methods. Nuvei also focuses on authorization optimization, fraud & risk management, chargeback resolution, and currency management. With integration options tailored for online retail, financial services, and gaming platforms, Nuvei supports businesses in maximizing their revenue and optimizing their tech stack. The company's global platform encompasses more than 700 diverse payment options, making it a trusted partner for both small to medium-sized businesses and large enterprises. Data Scientist – Payments Risk Analytics 🔥 0 minutes ago 🇺🇸 United States – Remote ⏰ Full Time 🟡 Mid-level 🟠 Senior 📊 Data Scientist Apply Now Find Hiring Managers Customize resume + cover letter Report problem ☆ Save ☑️ Mark as applied ❌ Hide 📋 Description
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. 🎯 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.
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Hard Skills & Tools

PythonSQLdata analysisexploratory data analysisfeature evaluationcohort analysisanalytical automationrisk decisioningfraud analyticsdecisioning performance analysis

Soft Skills

communicationanalytical thinkingproblem-solvingadaptabilitycollaborationstrategic thinkinginsight generationtrend detectionrecommendation translationoperating in ambiguity