Data Scientist

Overview

As a Data Scientist in our financial services practice, you will build and scale ML models and experiments to address real-world business challenges. You will join a cross-functional Data team to shape an AI-powered analytics platform and translate data into actionable insights. You will monitor model performance and champion MLOps practices to ensure scalable, compliant deployments. This role offers the chance to influence pricing, risk, and customer behavior through predictive analytics. You will work in a collaborative environment that values pragmatism and impact.

Responsibilities

• Design, train, and deploy production-ready ML models and statistical experiments
• Collaborate with Data Engineering and Analytics to build reproducible pipelines for a unified analytics platform
• Translate transactional data into actionable predictions and partner with Product, Marketing, and Finance
• Monitor model performance, guard against data drift, and promote MLOps best practices

Key requirements

• Proven experience building ML models in a commercial setting
• Expert-level Python skills (pandas, NumPy, scikit-learn) and solid statistical grounding
• Experience with cloud or modern data environments (Microsoft Fabric, Azure, Databricks)
• Clear, impactful communication bridging technical models and business outcomes

• clear communication
• collaboration
• business-focused problem solving
• Machine learning
• MLOps
• Python (pandas, NumPy, scikit-learn)

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