About this role.
Signifyd is seeking a Chargeback Data Analyst to investigate dispute and transaction data, identify chargeback trends, and improve recovery and fraud-prevention outcomes. The role combines SQL, Python, Databricks, and Looker-based analysis with dashboard development, metric governance, and operational process improvement. The analyst will partner closely with data science, BI, product, engineering, and merchant-facing teams to resolve root causes of avoidable chargebacks. Success requires at least two years of analytical experience, strong knowledge of card-network dispute rules, payment ecosystems, and careful handling of sensitive financial and consumer data.
Role DNA
A quick view of the complexity, pace, ownership and collaboration implied by the job description.
Job Complexity
4/5Pace & Pressure
4/5Autonomy Level
4/5Communication Load
4/5Salary analysis
Estimated compensation compared with the broader US market for similar roles.
Core skills
Skills and capabilities most closely associated with this opportunity.
Sample interview questions
I would first validate the metric definition and source-data quality, then segment chargebacks by reason code, merchant, processor, payment method, geography, product cohort, transaction date, and order attributes. I would compare the affected period with historical baselines, quantify material contributors, and investigate whether changes are linked to policy, product, operational, or fraud-pattern shifts. I would conclude with prioritized root-cause hypotheses and measurable remediation actions.
I would align with stakeholders on decisions the dashboard must support, then define validated metrics such as chargeback rate, win rate, recovery amount, response timeliness, reason-code mix, and backlog aging. I would create drill-downs by merchant, payment processor, network, market, and time period, document metric logic, and add data-quality checks. The dashboard should clearly distinguish trends from targets and enable owners to identify and act on exceptions quickly.
I would confirm the applicable network, reason code, dispute stage, and response deadline before validating that the evidence directly addresses the stated claim. I would check documentation completeness, consistency across transaction records, delivery or service proof, customer communication, and required formatting. If data is incomplete or conflicting, I would escalate promptly and document the decision trail to protect both compliance and recovery outcomes.
I would use SQL to efficiently extract, join, and aggregate transaction and dispute data from governed sources, then use Python for deeper analysis such as cohort comparisons, anomaly detection, statistical testing, or repeatable data-quality validation. I would publish the resulting logic in a documented workflow and share findings through a dashboard or concise stakeholder readout. This approach keeps analysis reproducible while making conclusions actionable.
I would lead with the business impact, such as the estimated loss, affected merchant segment, or change in dispute win rate, rather than the technical methodology. I would use a simple visual to show the pattern, explain the likely driver and confidence level, and recommend a specific action with an expected measurement plan. I would provide technical detail separately for teams that need to validate or implement the solution.
At Signifyd, we help merchants confidently grow their businesses by building trusted relationships with their customers. Our advanced technology, combined with a team genuinely invested in our clients’ success, creates frictionless shopping experiences, approving more good orders, protecting revenue, and keeping customers happy.
Trusted by thousands of leading merchants across more than 100 countries, we securely process billions of transactions each year. Our people are the heart of everything we do, driving our mission forward with commitment, empathy, and creativity. Join us on our mission to empower confident, fraud-free commerce by helping online retailers provide superior customer experiences and eliminate fraud. Learn about our company values here!
Position Overview
You’ll join our Chargeback Investigations team as a Data Analyst, serving as a front-line financial driver and data integrity gatekeeper for Signifyd. In this role, you will leverage data to uncover insights, optimize dispute strategies, and minimize financial losses while mitigating fraud and chargeback risks for our customers.
Using your skills in data analysis, trend identification, and chargeback research, you will help track recovery performance, ensure claims align with card network policies, and deliver actionable data to help merchants and internal teams optimize their workflows for success. This is a high-impact role offering tremendous opportunities for growth, learning, and cross-functional leadership.
What You’ll Do
- Work independently and with your team to help achieve the overall goals of the department.
- Gather feedback and complete research for new products, features and developments
- Enhance our operational workflows via process improvements and identification of automation opportunities.
- Oversee quality assurance checks on new features
- Support Product teams in different Product and feature launch stages, ensuring alignment on timelines, requirements and success criteria.
- Develop metrics and projections on large datasets to extract trends, measure results and outcomes, identify areas of opportunity, and predict future performance.
- Turn insights into compelling business cases and recommendations that drive action and support business decisions based on insights gained from your data analysis.
- Build analytical tools and dashboards to quantify the impact of Chargeback Investigations team initiatives and identify opportunities for improvement
- Develop a deep understanding of how existing metrics are calculated, and ensure metrics source data is reliable and measures our effectiveness at combating integrity issues
- Collaborate with data science, BI, and product teams, prioritize issue resolution, and establish and maintain an operating rhythm and accountability to identify and resolve.
- Partnering with engineering, product, and merchant teams to fix root-cause vulnerabilities that generate avoidable chargebacks.
Requirements
- Fluent in English (written and verbal).
- Minimum of 2 years of experience in data-driven analytical roles (e.g., financial analysis, product analytics, business intelligence, or risk/operations).
- Proven data analysis capabilities, with experience using quantitative data to identify chargeback trends, optimize dispute win rates, and drive operational decision-making.
- Knowledge and experience using SQL, Python, Databricks and Looker
- Hands-on experience with payment processors across LatAm, EMEA, or North America.
- In-depth knowledge of card network regulations (Visa, Mastercard, American Express, Discover) specifically surrounding chargeback cycles, dispute rights, and merchant/consumer guidelines.
- Strong analytical and problem-solving skills, with the ability to translate complex transaction datasets and dispute metrics into clear actionable insights.
- Highly professional and adaptable, capable of keeping pace with changing environments while maintaining strict adherence to Signifyd’s Security and Privacy policies.
- Strict discretion and confidentiality when handling sensitive consumer data, financial metrics, and payment details.
- Excellent time management and organizational skills, with a proven ability to prioritize heavy data workloads, multitask, and work flexible hours as needed.
- Collaborative team player with a proactive attitude, comfortable executing independent data investigations as well as collaborating cross-functionally to improve chargeback processes.
Highly Desired
- Experience using a variety of payment platforms or processors across (e.g. Shopify, Stripe, PayPal, Adyen, Braintree)
- Experience analyzing transaction logs, chargeback documentation, and complex datasets.
- Proven track record of directly improving chargeback win rates or reducing overall chargeback-to-transaction ratios.
- Prior experience using automated chargeback management platforms or merchant portals (e.g., Ethoca, Verifi/Order Insight, Chargebacks911, Kount).
- Familiarity with local and alternative payment methods in key markets (e.g., Pix in LatAm, iDEAL or Klarna in EMEA) and their specific dispute mechanisms.
#LI-Remote
Benefits in Mexico:
- Health, Dental & Vision Insurance
- Life Insurance of 24 months salary
- Annual Performance Bonus
- Christmas Bonus of 1 Month’s Salary
- Food Vouchers
- Stock Options
- Paid Parental Leave
- Flexible Work Arrangements
- Telework Stipend for Home Internet
- 12 Paid Vacation Days with 85% Vacation Premiums
- Paid Holidays
- Company Social Events
- Signifyd Swag
- Dedicated learning budget through Learnerbly
- On-Demand Therapy for all employees & their dependents
We want to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.
Annual salary information is not provided for this position. Explore salary ranges for similar roles in our Salary Directory ›
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