Senior Data Scientist, RC Capital

Senior Data Scientist, RC Capital in Canada.

This role offers the opportunity to be the founding Data Scientist within a fast‑growing fintech initiative focused on scaling innovative financial products for mobile developers. This work will design and own the core data science strategy powering underwriting, fraud detection, and risk modeling from the ground up. Your models will directly influence real financial decisions tied to high‑volume global app revenue streams.

You will collaborate closely with Product and Engineering teams to embed data‑driven risk intelligence into production systems. This position shapes how capital is deployed safely and efficiently in a fast‑moving, ambiguous environment, defining technical foundation and long‑term vision for a new financial product line.

Accountabilities

Own and define the data science strategy for underwriting, fraud detection, and lead qualification systems from inception to production‑scale deployment.

Build, validate, and maintain advanced machine learning models that assess financial risk using real‑time, cross‑platform revenue and behavioral data.

Develop anomaly detection and fraud prevention systems that safeguard financial transactions while enabling business growth.

Partner with Product and Engineering to integrate risk signals into decision engines and customer‑facing workflows.

Analyze large‑scale datasets to generate insights that improve credit models, product design, and financial decisioning frameworks.

Establish performance measurement frameworks to track model effectiveness and continuously improve predictive accuracy and business impact.

Requirements

5+ years of experience in data science, ideally within fintech, credit, lending, payments, or similarly risk‑intensive domains.

Strong expertise in fraud detection, underwriting, or risk modeling with demonstrated experience in financial decision systems.

Advanced proficiency in SQL and Python, with experience building, deploying, and monitoring production machine learning models.

Strong understanding of statistical modeling, machine learning techniques, and real‑world data constraints in financial contexts.

Familiarity with mobile app ecosystems or subscription‑based digital products is highly desirable.

Proven ability to operate independently in ambiguous environments, making high‑impact decisions with limited information.

Strong systems thinking mindset with the ability to scale solutions and identify automation opportunities.

Ownership mentality with a strong bias for action, execution, and measurable impact.

Benefits

Competitive equity package in a high‑growth, Series C‑backed organization supported by leading investors.

Fully remote and flexible work environment across global locations.

4–5 weeks of recommended annual time off for rest and recharge.

$2,000 USD home office setup allowance.

$1,000 USD annual learning and development stipend.

Long‑term 10‑year window to exercise vested equity options.