Lead – POC Data Science

This is a fully remote position, open to applicants in United States.

📋 Description

• Lead and cultivate a team of individual contributor data scientists — establish direction, remove obstacles, conduct 1:1 meetings, and enhance each individual's scope and impact.

• Take ownership of POC/POV delivery — collaborate directly with enterprise clients to showcase fraud-loss reduction and platform ROI, from the initial data extraction to stakeholder presentations.

• Remain actively involved in technical tasks — develop or review machine learning models, perform comprehensive fraud analyses, and deliver production-quality solutions alongside your team.

• Define and monitor performance metrics — create dashboards and reporting frameworks to evaluate the effectiveness of risk strategies for various clients.

• Convert client challenges into data-driven solutions — serve as a senior contact for fraud-related issues, transforming complex insights into straightforward recommendations.

• Collaborate cross-functionally with Engineering, Product, and GTM teams to define project scopes, influence the roadmap, and ensure that fraud solutions and models are implemented and scaled appropriately.

• Facilitate experimentation — support A/B testing to safely validate new strategies prior to full implementation.

• Elevate professional standards — mentor individual contributor data scientists on modeling excellence, effective data storytelling, and client communication.

⛳️ Requirements

• Over 10 years of experience in fraud/risk data science and analytics, demonstrating significant impact in fraud, payments, or fintech sectors.

• More than 3 years in a leadership role (team lead, manager, or tech lead with direct reports) — experience in coaching data scientists and facilitating their growth.

• Strong hands-on technical expertise — proficiency in Python and SQL is essential; experience with Spark, Kafka, or feature stores is advantageous.

• Proven experience in delivering POC/POV engagements with quantifiable customer outcomes.

• Established track record in applied machine learning within fraud or risk contexts — including anomaly detection, classification, and graph analytics in live environments.

• Expertise in business intelligence and dashboarding tools — such as Sigma, Tableau, Metabase, or similar platforms.

• Excellent communication and stakeholder management skills — capable of translating complex model results for both technical and non-technical stakeholders, including clients and executives.

• Proactive and ownership-driven — you take initiative and don’t wait for obstacles to be resolved.

• Familiarity with real-time decision-making infrastructure (Flink, Kafka, feature stores) is a plus.

• Experience in a high-growth fintech, payments, or financial institution is a plus.

🏝️ Benefits

• Competitive compensation package in cash and equity.

• Early exercise option for all stock options, including those that are pre-vested.

• Flexible work arrangements: Remote-first culture.

• Generous paid time off and year-end break.

• Comprehensive health insurance, dental, and vision coverage for employees and their dependents - *specific to US and Canada*.

• 4% matching in 401k / RRSP - *specific to US and Canada*.

• A MacBook Pro sent directly to your home.

• One-time stipend to establish a home office — covering desk, chair, screen, etc.

• Monthly meal stipend.

• Monthly stipend for social meet-ups.

• Annual health and wellness stipend.

• Annual learning stipend.