Data Scientist, Alternative Finance

About the Role

As a Data Scientist in Alternative Finance, you will partner with senior team members to transform complex raw data into actionable business insights and predictive models. This role offers hands-on experience across the end-to-end data science lifecycle, including dataset curation, decision strategy development, model deployment audits, and performance monitoring across diverse domains.

What You Will Do

• Problem Solving & Analysis: Apply hypothesis-driven methodologies to dissect complex analytical challenges, synthesize structured and unstructured datasets, and extract actionable insights.
• Model Development: Train, evaluate, and fine-tune predictive models and decision frameworks (e.g., logistic regression, ensemble tree models, neural networks) to address strategic business needs.
• Quality & Attention to Detail: Rigorously audit data inputs, participate in peer code reviews, and conduct comprehensive model evaluations and performance monitoring.
• Collaboration & Communication: Collaborate within cross-functional teams, maintain clear documentation of analytical tasks, and effectively communicate key findings to technical and non-technical audiences.

Requirements & Tech Stack

• Analytical Thinking: Proactive analytical thinker with a passion for structured problem-solving, high standards for data quality, and a commitment to continuous learning.
• Core Skills:
• Strong analytical and quantitative skills.
• Proficiency in statistical programming (Python or R) and SQL.
• Solid understanding of key machine learning algorithms, data manipulation, and modern software engineering practices (e.g., Git/version control).

Qualifications

• Education: Master’s degree or higher in a STEM field (Data Science, Computer Science, Statistics, Mathematics, Engineering) or equivalent practical experience.
• Experience: 0–2 years of experience in an analytical or data science role, including academic or project-based experience developing predictive models.

What Could Set You Apart

• Master’s degree or higher in a quantitative discipline.
• Experience developing AI skills or using AI agents and tools to code and build applications or gems.
• Experience with cloud platforms (AWS, GCP, or Azure) or cloud analytics tools.
• Practical project portfolio demonstrating end-to-end model development and rigorous data validation.