Lead – POC Data Science

Sardine

Lead Data Scientist managing proof of concept projects for fraud prevention and analytics. Collaborating with enterprise customers and developing scalable machine learning solutions.

Posted 6/3/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $160,000 - $270,000 per yearWebsite

ATS Keywords

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Hard Skills

PythonSQLSparkKafkamachine learninganomaly detectionclassificationgraph analyticsdashboardingdata analysis

Soft Skills

leadershipcommunicationstakeholder managementmentoringproblem-solvingcollaborationstorytelling with dataownershipaction-orientedcoaching

Tools & Technologies

SigmaTableauMetabaseA/B testingreporting frameworksdata solutionsPOCPOVdashboardsproduction-grade solutions

Industry Keywords

fraudriskdata scienceanalyticspaymentsfintechperformance metricsclient communicationcross-functional collaborationexperiment validation

Tech Stack

Tools & technologies

KafkaPythonSparkSQLTableau

About the role

Key responsibilities & impact

Lead and develop a team of IC data scientists — set direction, unblock work, run 1:1s, and grow each person's scope and impact
Own POC/POV delivery — partner directly with enterprise customers to demonstrate fraud-loss reduction and platform ROI, from first data pull through to stakeholder readout
Stay hands-on in the technical work — build or review ML models, conduct in-depth fraud analyses, and ship production-grade solutions alongside your team
Define and track performance metrics — design dashboards and reporting frameworks to measure the effectiveness of risk strategies across clients
Translate client problems into data solutions — act as a senior point of contact for fraud challenges, turning complex findings into clear recommendations
Partner cross-functionally with Engineering, Product, and GTM to scope work, influence the roadmap, and ensure fraud solutions and models get instrumented and scaled correctly
Drive experimentation — support A/B testing to safely validate new strategies before full rollout
Raise the bar on craft — mentor IC data scientists on modeling rigor, storytelling with data, and client communication

Requirements

What you’ll need

7–10 years of experience in fraud/risk data science and analytics with demonstrated impact in fraud, payments, or fintech
2–3 years in a people leadership role (team lead, manager, or tech lead with direct reports) — you've coached data scientists and helped them grow
Strong hands-on technical skills — Python and SQL are essential; Spark, Kafka, or feature stores are a plus
Experience delivering POC/POV engagements with measurable customer outcomes
Proven track record with applied ML in fraud or risk — anomaly detection, classification, and graph analytics in production
Expertise in BI and dashboarding — Sigma, Tableau, Metabase, or equivalent
Strong communication and stakeholder management — able to translate complex model outputs for both technical and non-technical audiences, including clients and execs
Bias toward action and ownership — you don't wait to be unblocked

Benefits

Comp & perks

Generous compensation in cash and equity
Early exercise for all options, including pre-vested
Work from anywhere: Remote-first Culture
Flexible paid time off and Year-end break
Health insurance, dental, and vision coverage for employees and dependents - *US and Canada specific*
4% matching in 401k / RRSP - *US and Canada specific*
MacBook Pro delivered to your door
One-time stipend to set up a home office — desk, chair, screen, etc.
Monthly meal stipend
Monthly social meet-up stipend
Annual health and wellness stipend
Annual Learning stipend