Data Scientist-POC (Remote - North America)

This position is posted by Jobgether on behalf of Sardine. We are currently looking for a Data Scientist-POC in North America.

This role offers a unique opportunity to directly shape how organizations detect and prevent fraud using cutting-edge data science techniques. The Data Scientist-POC will work on real-world challenges, designing, prototyping, and deploying machine learning and graph analytics solutions to stop fraud and mitigate risk. You will collaborate closely with clients and engineering teams to deliver high-impact, production-ready models while standardizing workflows and ensuring scalability. Ideal candidates thrive in fast-paced, remote-first environments, are highly self-motivated, and enjoy translating complex data into actionable insights that drive tangible business outcomes. This position balances hands-on technical work with client-facing responsibilities, providing an environment where innovation and problem-solving are highly valued.

Accountabilities

• Build and deploy machine learning models and data-driven solutions to detect and prevent fraud across diverse financial and fintech use cases.
• Work closely with clients to understand fraud challenges and deliver proof-of-concept and production-ready solutions.
• Standardize modeling workflows and collaborate with engineering teams to integrate and scale models in production.
• Develop risk metrics, datasets, and causal impact analyses to improve fraud detection and mitigation strategies.
• Champion a data-first approach across internal teams, promoting clarity, rigor, and impact.
• Monitor and optimize model performance while ensuring data quality and compliance with standards.
• Communicate technical findings clearly to both technical and non-technical stakeholders.

• 7+ years of experience in data science, quantitative modeling, or a related field, ideally within risk or fraud contexts.
• Advanced degree in a quantitative discipline (Mathematics, Statistics, Computer Science, Engineering, Economics, etc.).
• Strong proficiency with Python, R, Spark, SQL, or equivalent tools for data analysis and modeling.
• Experience in building, deploying, and maintaining machine learning models in production environments.
• Strong problem-solving, critical thinking, and creative solution design skills.
• Excellent communication skills with the ability to convey complex findings to clients and stakeholders.
• Self-motivated, collaborative, and able to thrive in a remote-first, distributed team environment.

• Competitive base salary: $150,000 – $180,000 plus equity with significant upside potential.
• Remote-first culture with flexibility to work from anywhere in North America.
• Generous paid time off including flexible PTO, year-end break, and self-care days.
• Health, dental, and vision coverage for employees and dependents (US and Canada specific).
• Retirement plan matching (401k in the US, RRSP in Canada).
• MacBook Pro delivered to your home and one-time home office setup stipend.
• Monthly meal and social meet-up stipends, plus annual learning and wellness stipends.
• Access to expert financial advisory and opportunities to collaborate with world-class professionals globally.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly:
🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.
📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.
🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.
🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role.
Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.

Thank you for your interest!

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