Lead PoC Data Scientist at Sardine – Remote - USA or Canada | Jobyssey

You will drive critical proof of concept PoC projects for enterprise customers and financial institutions while developing your team’s craft and accelerating impact. You will be hands on building or reviewing ML models, conducting fraud analyses, and shipping production ready solutions using fraud analytics and machine learning. You will own a mix of client facing PoC/POV delivery, ML product development, and team performance, collaborating with engineering product and GTM to scale fraud solutions.

Responsibilities

Lead and develop a team of IC data scientists to set direction unblock work, run 1:1s, and grow each person's scope and impact
Own POC/POV delivery by partnering directly with enterprise customers to demonstrate fraud loss reduction and platform ROI from first data pull through to stakeholder readout
Stay hands on by building or reviewing ML models, conducting in depth fraud analyses, and shipping production grade solutions alongside your team
Define and track performance metrics by designing dashboards and reporting frameworks to measure the effectiveness of risk strategies across clients
Translate client problems into data solutions and 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 are instrumented and scaled correctly
Drive experimentation by supporting A/B testing to safely validate new strategies before full rollout
Raise the bar on craft by mentoring IC data scientists on modeling rigor storytelling with data and client communication

Requirements

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
Nice to have Familiarity with real-time decision infrastructure (Flink, Kafka, feature stores)
Nice to have Background in a high-growth fintech payments or financial institution

Benefits

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

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Benefits