Product Data Scientist (Fintech)

TL;DR

Product Data Scientist (Fintech): Building and evolving predictive engines to power a high-growth fintech company with an accent on quality of service, liquidity management, risk, and operational decision-making. Focus on translating ambiguous business problems into scalable data products, ensuring predictions are actionable and embedded into real workflows.

Location: Singapore, Central, Singapore

Company

hirify.global is the Smart Superhighway for money movement around the world.

What you will do

• Ensure production ready implementation of ML projects, including writing production-grade data transformations and building automated training / inference pipelines.
• Wrap models in inference scripts and register them in model registry.
• Implement rigorous model interpretability frameworks to ensure every prediction can be explained to non-technical stakeholders.
• Participate in the design and analysis of A/B tests to validate the business impact of model deployments.
• Ensure timely delivery of high-quality, testable, reproducible, and documented code using GitLab and best practices like Data Versioning and Feature Stores.
• Understand, apply, and champion the principles of rigorous statistical analysis and communicate error metrics clearly to non-technical stakeholders.

Requirements

• Holding a degree in Statistics, Mathematics, Computer Science, Economics, or related quantitative fields.
• 5+ years of relevant industry experience, with a preferred background in Fintech, Payments, or Financial Services.
• Deep expertise in Time-Series Forecasting and understanding of non-stationarity, seasonality, and backtesting strategies.
• Proficient in Python and core ML libraries: Mastery of Scikit-Learn, XGBoost, and Pandas / Polars.
• Deep expertise in SHAP (Shapley Values), LIME, or Counterfactual Explanations.
• Proficient in cloud native AI tech stack: Deep hands-on experience with cloud native ML ecosystem (e.g. AWS SageMaker, Feature Store, Model Registry, GCP Vertex AI, Feature Store, Model Registry).

Nice to have

• Certifications: AWS Certified Machine Learning - Specialty is highly preferred.

Culture & Benefits

• Operate at the intersection of data science, product thinking, and business outcomes, combining a startup mindset with the rigor required of a regulated financial institution.
• Partner with a wide range of stakeholders to translate ambiguous business problems into scalable data products.
• Define success metrics, challenge assumptions, and continuously refine models based on business feedback and changing market conditions.
• Be responsible for the quality of your deliverables.
• Passionate about code quality and reproducibility: Strict adherence to Git, code reviews, and environment management.
• Interest in the Fintech Industry and market innovations.