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Achieve · 6 hours ago

Sr. Data Scientist (Fraud Analyst)

San Mateo, CA

Full-time

Hybrid

Mid, Senior Level

$150K/yr - $185K/yr

3+ years exp

Achieve is a leading digital personal finance company that provides innovative financial solutions. They are seeking a highly analytical Sr. Data Scientist / Fraud Rules & Strategy Analyst to develop and maintain fraud detection rulesets while collaborating with vendors and cross-functional teams to enhance fraud prevention strategies.

Financial Services

No H1B

Responsibilities

Design, implement and maintain the fraud-detection and prevention rulesets across our transaction flows, updates made iteratively in an agile fashion (frequent, incremental rule releases)

Monitor rule performance (false-positives, false-negatives, operational metrics) and adjust rules to optimize detection and minimize business friction

Execute ad hoc analysis of fraud trends, emerging typologies, and root‐cause investigations to identify opportunities for new or updated rules

Work closely with vendors (fraud-detection/analytics platform providers, third-party intelligence services) to incorporate current industry thinking and best practices into our strategy

Develop dashboards and reports in Tableau to visualize key fraud metrics, rule performance, business impact and risk exposure

Write SQL queries and Python scripts to interrogate transaction, alert and case data; build prototypes of new rules, test and deploy them

Collaborate cross-functionally with Product, Operations and Compliance teams to align fraud-prevention initiatives with business goals and regulatory requirements

Participate in sprint planning, retrospectives and backlog grooming to ensure fraud-rule work is aligned with the agile roadmap

Maintain documentation of rule logic, assumptions, test results and versioning; ensure auditability and traceability of rule changes

Stay apprised of fraud-prevention industry trends, vendor technology updates, and regulatory developments; provide recommendations to senior leadership for strategy refinement

Qualification

Fraud detectionSQLPythonTableauData analysisAgile methodologyCommunication skillsProblem-solving skillsAttention to detailCritical thinking

Required

Bachelor's degree in quantitative discipline (e.g., Computer Science, Data Science, Finance, Economics, Mathematics) or equivalent

Minimum of 3 years of hands-on experience in fraud detection, fraud analytics, risk management or a related role (preferably in payments, fintech, e-commerce or banking)

High level of proficiency in SQL and Python for data manipulation, data interrogation, scripting and rule prototyping

Proven experience with Tableau (or equivalent business-intelligence tools) to build dashboards and visualizations

Experience designing, deploying and maintaining fraud-detection rules/rule engines (or equivalent controls) and analyzing the results

Experience interacting with vendor solutions, engaging external partners or bringing in external intelligence to inform strategy

Excellent analytical, problem-solving and critical-thinking skills with attention to detail

Strong verbal and written communication skills – able to translate technical detail into actionable insights for business stakeholders

Comfortable working in an agile environment: attending sprint ceremonies, prioritizing tasks, responding to changing requirements

Ability to work independently, manage multiple concurrent rule-updates and investigations, while balancing business-friction vs risk mitigation trade-offs