Data Science Lead

Inizio Partners Corp-posted about 13 hours ago

Full-time • Mid Level

Hybrid • Malvern, PA

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We are seeking a experienced Data Science Lead - Fraud Strategy to join our Fraud Strategy Practice. This role oversees recommendation, development, implementation and monitoring of fraud strategies while preserving customer experience and achieving operational efficiency. It involves utilizing statistical and predictive analytics, machine learning, and data visualization to design prevention strategies, provide actionable insights and consult with business leaders on leveraging these insights for strategic decision-making.

Lead design and execution of end-to-end fraud strategies across key financial products and channels (e.g., new account onboarding, ATO, money movement in retail and card products).
Own recommendation, development, deployment, and optimization of fraud detection rules and logic in advanced platforms such as ThreatMetrix, ensuring high detection accuracy and minimal customer friction.
Perform hands-on delivery as needed and guide a team of analysts in conducting deep-dive analytics and exploratory data mining using structured and unstructured data to uncover emerging fraud trends.
Manage fraud KPIs (e.g., detection rate, prevention rate, false positives, loss capture, good user declines), and regularly review performance to inform strategy adjustments.
Translate business risk appetite into actionable fraud controls, leveraging both historical data and forward-looking risk signals.
Drive strategic roadmap planning for fraud mitigation capabilities, including signal enrichment, tooling improvements, and scenario testing frameworks.
Lead project management effort as warranted through structuring business requests and translating requirements into an analytic approach.
Making recommendations to key business partners or senior management as needed.
Partner cross-functionally with Product, Engineering, Fraud Ops, Risk, and Compliance to align on detection strategies, rule deployment, operational triggers, and customer experience impact.
Perform post-incident reviews and own the development or amendment to existing strategies based on root cause findings.
Present insights, performance updates, and strategic recommendations to senior stakeholders and governance forums.
Stay ahead of evolving fraud typologies, regulatory requirements, and industry trends; proactively embed learnings into strategic planning.

7+ years related work experience in fraud strategy or fraud data science field with building strategies or models in banking industry.
Experience in leading fraud strategy mandate in retail banks and consumer cards with thought leadership to drive client priorities successfully.
Understanding of statistical methods, including classical statistics, probability theory, econometrics, and time-series analysis.
High proficiency with SQL and Python.
Working knowledge of Hive, Spark, AWS Sagemaker.
Undergraduate degree or equivalent combination of training and experience.
Proven expertise in fraud rule development and strategy implementation with LexisNexis fraud solutions or comparable solutions (e.g., Actimize, etc).
Strong verbal and written communication skills, especially in client-facing or cross-functional settings.

Experience with ThreatMetrix rule creation and management is a big plus.
Experience with machine learning is a plus.
Experience in setting or managing fraud loss appetite and performance planning.
Background in consulting or client advisory roles in fraud strategy.

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