Principal Data Scientist

About the role

The Principal Data Scientist is a senior technical leader who designs and delivers high‑impact data science and AI solutions for both clients and internal business units. The role combines deep machine‑learning expertise with strong software‑engineering practices, guiding initiatives from discovery through production while remaining hands‑on.

Key responsibilities

• Define technical direction for complex, high‑value AI projects, aligning choices with business strategy, risk appetite, and measurable outcomes.
• Lead end‑to‑end delivery: opportunity identification, problem framing, data assessment, experimentation, deployment, adoption, monitoring, and continuous improvement.
• Architect and build scalable, maintainable Python‑based ML/AI solutions for structured and unstructured data, applying rigorous software‑engineering standards.
• Establish evaluation frameworks, baselines, and acceptance criteria to assess model performance, reliability, fairness, drift, operational readiness, and business impact.
• Act as a trusted technical advisor, translating ambiguous business needs into executable roadmaps and communicating options, trade‑offs, and recommendations to senior stakeholders.
• Lead technical workstreams, architecture reviews, delivery planning, dependency and risk management, balancing quality, speed, cost, and operational constraints.
• Mentor data scientists and engineers, raise standards through reusable patterns, code reviews, documentation, and knowledge sharing.
• Collaborate with data‑engineering, MLOps, platform, product, and application teams to create reusable data, feature, training, evaluation, and inference capabilities.
• Embed responsible AI, security, privacy, model governance, and regulatory requirements throughout the solution lifecycle.

Required profile

• Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or Engineering (or equivalent professional experience).
• 9–12 years of hands‑on experience delivering data‑science, machine‑learning, or AI solutions with a proven record of technical leadership.
• Demonstrated ability to influence senior stakeholders, shape solution propositions, and drive measurable enterprise outcomes.

Required skills

• Python
• Machine Learning
• Artificial Intelligence
• Software Engineering
• Data Science
• Model Evaluation & Monitoring
• Model Governance & Responsible AI
• MLOps
• Data Engineering