Data Science - Payments or Fraud Analytics

Straive is a global leader in enterprise-grade data analytics and AI solutions, committed to empowering businesses across various industries with cutting-edge technology and expert insights. Backed by EQT, a top private equity firm, we are uniquely positioned to drive innovation through significant investments and an entrepreneurial spirit.

Our core focus is on delivering advanced Data Analytics & AI Solutions. By combining sophisticated technology with subject matter expertise, we deliver material impact on our clients' topline and streamline their operations. We specialize in providing tailored solutions across financial services, CPG, legal, pharma, life sciences, retail and logistics, helping them build robust data analytics and AI capabilities.

With a client base spanning 30 countries, Straive's strategically located teams operate from eight countries and is headquartered in Singapore. This global presence enables us to offer localized expertise with a worldwide perspective.

Join Straive to be part of a dynamic team at the forefront of data analytics and AI innovation. Here, you'll have the opportunity to contribute to transformative projects, supported by significant investments and an entrepreneurial drive fueled by our partnership with EQT.

Website: https://www.straive.com/

Job Role: Data Science - Payments or Fraud Analytics

Location: San Jose, CA (Hybrid)

Job Type: Full-time

About the Role

We are seeking a strong, hands-on Senior Analyst with deep experience in the payments space to join ’s Analytics team in San Jose. This role will focus on driving insights and strategies across credit/debit card payments and fraud, partnering closely with product, risk, and business stakeholders.

You will use your expertise in SQL, Tableau, and analytical problem solving to identify trends, diagnose issues, and recommend data-driven solutions that improve authorization rates, reduce fraud losses, and enhance customer experience.

Key Responsibilities

• Analyze large-scale payments and fraud datasets (with a focus on credit/debit card transactions) to identify patterns, trends, and anomalies.
• Develop and track key performance metrics for payments performance, fraud/risk, and customer experience.
• Build dashboards and reports in Tableau to provide clear, actionable insights to business and leadership teams.
• Partner with Product, Risk, Operations, and Engineering to define problems, size opportunities, and recommend data-driven strategies.
• Design and execute deep-dive analyses and A/B tests to evaluate the impact of product, policy, or strategy changes.
• Translate complex analytical findings into clear narratives and recommendations for non-technical stakeholders.
• Support or collaborate on modeling, BI, or strategy initiatives related to payments optimization and fraud mitigation.
• Ensure data quality, consistency, and proper documentation of analytical work.

Required Qualifications

• 5+ years of total analytics experience in the payments space, ideally within card networks, issuers, acquirers, PSPs, or large fintechs.
• Strong domain exposure to credit/debit card payments; fraud/risk analytics experience strongly preferred.
• Advanced proficiency in SQL (complex joins, window functions, performance optimization).
• Strong hands-on experience with Tableau (or similar BI tools) for dashboarding and data visualization.
• Proven track record in at least one of the following areas:
• Modelling (risk/fraud/propensity/segmentation)
• Business Intelligence / Reporting
• Strategy / Product Analytics
• Demonstrated ability to structure ambiguous problems, perform rigorous analysis, and drive to clear recommendations.
• Strong communication skills with the ability to influence cross-functional stakeholders.
• Bachelor’s degree in a quantitative field (e.g., Statistics, Mathematics, Economics, Engineering, Computer Science) or equivalent practical experience.

Preferred Qualifications

• Experience in a global payments or large-scale fintech environment (e.g., card networks, major banks, PSPs).
• Familiarity with fraud tools, risk decision engines, or chargeback processes.
• Experience with experimentation (A/B testing) and causal inference methods.
• Exposure to Python/R or similar for advanced analytics or modeling.
• A master's degree in a quantitative discipline is a plus.

What We’re Looking For

• A strong, hands-on analyst who is comfortable owning complex problems end-to-end.
• Someone who thrives in a fast-paced environment and can balance detail-oriented analysis with business impact.
• A collaborative partner who can work effectively with product, risk, and engineering teams to turn data into decisions.

If you have deep payments experience, strong SQL and Tableau skills, and a passion for solving complex fraud and payments problems, we’d like to hear from you.

This job description is not intended to cover or contain a comprehensive listing of all responsibilities, duties, or activities that ar