Head Data Scientist

Role & responsibilities

• Define and execute the data science and AI strategy aligned with business goals.
• Lead, mentor, and manage data scientists, machine learning engineers, and analytics teams.
• Oversee the design, development, testing, and deployment of machine learning and deep learning models.
• Drive the adoption of Generative AI, Large Language Models (LLMs), predictive analytics, and automation solutions.
• Develop scalable data science solutions to improve business performance, customer experience, and operational efficiency.
• Collaborate with engineering, product, and business teams to identify opportunities for data-driven innovation.
• Establish best practices for model development, validation, deployment, monitoring, and MLOps.
• Ensure data quality, model reliability, data privacy, and responsible AI governance.
• Communicate analytical findings and strategic recommendations to senior leadership and business stakeholders.
• Manage project roadmaps, resource allocation, budgets, and delivery timelines.
• Evaluate emerging AI technologies and identify opportunities to improve products and business processes.

Preferred candidate profile

• Bachelor's or master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field.
• PhD in a relevant discipline is an advantage for research-focused roles.
• Typically 5 to 12 years of relevant experience for a Head of Data Science position; candidates with 5 to 10 years may be considered based on leadership experience and technical expertise.
• Strong proficiency in Python, SQL, statistics, machine learning, deep learning, and predictive modelling.
• Hands-on experience with frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Experience with Generative AI, LLMs, NLP, and AI-powered applications.
• Knowledge of cloud platforms such as AWS, Microsoft Azure, or Google Cloud.
• Experience with MLOps, model deployment, data pipelines, and large-scale data processing.
• Proven ability to lead technical teams, manage complex projects, and deliver measurable business outcomes.
• Strong strategic thinking, analytical problem-solving, and stakeholder management skills.
• Excellent written and verbal communication skills.
• Ability to work independently and lead distributed teams in a remote environment.