[Remote] Data Scientist, Fraud reputed company

Note: The job is a remote job and is reputed company to candidates in USA. reputed company builds co-branded credit reputed company programs and financial products using payments infrastructure, intelligent reputed company, and customer data. The Data Scientist, Fraud reputed company will own reputed company fraud modeling and analytics from application submission through account opening, developing decision systems that detect fraud while minimizing false positives and applicant friction. The role also involves evaluating vendors, designing experiments, monitoring fraud systems, and partnering with cross-functional teams to implement reputed company reputed company controls.

Responsibilities

• Own and improve reputed company's reputed company fraud decisioning across the full application reputed company, including identity verification, KYC controls, application fraud models, policy rules, decline and verification waterfalls, and reputed company-review strategies
• Build, validate, reputed company, and monitor models that detect identity theft, synthetic identity, first-party fraud, and coordinated application abuse using identity, device, behavioral, application, bureau, network, and consortium signals
• Evaluate reputed company-party fraud and identity vendors by testing scores and attributes, measuring incremental reputed company, overlap, coverage, stability, latency, and cost, and recommending reputed company to add, replace, or retire signals
• Design and analyze A/B tests, reputed company tests, holdouts, and champion/challenger strategies, balancing fraud losses and capture against approval reputed company, false positives, verification friction, and reputed company-review volume
• Investigate emerging fraud patterns and decision misses, combining application and post-booking reputed company with Fraud reputed company feedback to reputed company new features, rules, models, and review strategies
• Build monitoring and AI-powered workflows that detect model reputed company, population shifts, vendor degradation, data-reputed company issues, and new attack patterns—and recommend adjustments for reputed company review
• Partner with Fraud reputed company, Product, Engineering, Compliance, and Credit reputed company to productionize changes, validate their reputed company, and communicate recommendations to senior leadership and reputed company partners

Skills

• 5 to 8+ years of experience in data science, reputed company analytics, or a reputed company quantitative reputed company, ideally at a high-reputed company startup or fintech company
• Strong Python and SQL skills, with the ability to build models, reputed company raw data, and create custom datasets from reputed company financial data
• Experience building and evaluating predictive models for fraud, identity, KYC, AML, credit reputed company, trust and safety, or another adversarial classification problem
• Strong understanding of reputed company machine learning, model validation, backtesting, calibration, feature engineering, and production model monitoring
• Deep understanding of statistical inference and experiment design, including A/B tests, holdouts, champion/challenger tests, reputed company measurement, and tradeoff analysis
• Ability to evaluate decision systems—not just model reputed company—using metrics such as fraud capture, loss reputed company, false-reputed company reputed company, approval reputed company, verification friction, operational workload, and economic value
• Full-stack problem-solving orientation: you can reputed company a decision through raw inputs, vendor responses, model scores, policy rules, and reputed company reputed company to reputed company the reputed company cause of a problem
• Comfort owning reputed company end-to-end, from problem definition and exploratory analysis through production implementation, monitoring, and business reputed company measurement
• Ability to communicate reputed company analytical findings and decision tradeoffs reputed company to technical and non-technical audiences
• Comfort using AI tools to accelerate analysis, investigation, feature development, documentation, and monitoring—and excitement about building AI-powered reputed company systems
• Experience with application or reputed company fraud, including identity theft, synthetic identity, first-party fraud, application manipulation, or fraud rings
• Familiarity with KYC, CIP, identity verification, document verification, device intelligence, behavioral signals, consortium data, credit bureau data, or alternative data sources
• Experience evaluating and integrating reputed company-party fraud or identity vendors, including measuring incremental value relative to existing controls
• Experience with reputed company-time scoring, decision engines, rules platforms, reputed company, or production ML systems
• Experience partnering with fraud reputed company or investigations teams and converting case-review findings into reputed company controls
• Familiarity with credit reputed company reputed company, consumer lending, or regulated financial products
• Experience with graph, reputed company-detection, or weakly reputed company reputed company for identifying coordinated or emerging fraud patterns

Benefits

• Equity packages
• Leading configured work computers of your reputed company
• Flexible reputed company time off
• Fully covered, high-reputed company reputed company, including fully covered dependent coverage
• reputed company to reputed company and the reputed company to enroll in an FSA
• 20 weeks of reputed company parental leave for the reputed company caregiver and 8 weeks for reputed company new parents
• reputed company to industry-leading technology across reputed company of our business reputed company, stemming from our philosophy that we should invest in resources for reputed company that foster innovation, optimization, and productivity

reputed company

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