Head of Data Science

About the Role:

What You’ll Do:

• Define and drive the data science strategy, roadmap, and priorities.
• Lead, mentor, and grow a world-class team of data scientists, ML engineers, and analysts.
• Serve as an AI/ML thought leader, introducing innovations that enhance product and operational performance.
• Oversee development of models for credit underwriting, risk scoring, fraud detection, forecasting, customer segmentation, and the full credit lifecycle.
• Ensure production-grade deployment, monitoring, and optimization of ML models.
• Partner with product and engineering teams to integrate ML solutions into user-facing applications and internal decisioning engines.
• Work closely with compliance and risk teams to ensure fairness, explainability, and regulatory alignment.
• Support the development of scalable data pipelines and ML infrastructure.
• Establish best practices for data governance, reproducibility, version control, and feature engineering.
• Define and track KPIs demonstrating the business impact of data science initiatives.
• Promote a culture of experimentation, A/B testing, and continuous improvement.

What You’ll Bring:

• 10+ years’ experience in data science/ML, including 3+ years in leadership roles.
• Strong background in supervised/unsupervised learning, deep learning, and statistical modelling.
• Proven experience in fintech or financial services (credit, lending, fraud, risk, etc.).
• Advanced programming skills in Python, R, or Scala; familiarity with TensorFlow, PyTorch, and scikit-learn.
• Strong SQL and data visualization capabilities.
• Experience with big data technologies (Spark, Snowflake, Databricks) and cloud platforms (AWS, Azure, GCP).
• Demonstrated success deploying data products at scale.
• Strong leadership, communication, and stakeholder engagement skills.
• Strategic thinker with the ability to align data initiatives with organizational goals.
• Highly analytical with excellent problem‑solving skills and attention to detail.
• Ability to thrive in fast-paced, dynamic, high‑growth environments.
• Master’s or PhD in Computer Science, Statistics, Applied Mathematics, or related fields preferred.
• Experience with alternative data models, credit scoring, explainable AI (XAI), ethical AI, and model governance is advantageous.
• Startup or high-growth experience is a plus.