Senior/Lead Data Scientist

About the role

A leading telecommunications and digital services provider is looking for a Senior/Lead Data Scientist to accelerate its AI and data analytics capabilities. The role leads large-scale AI and machine learning programmes, defines strategic roadmaps and translates business priorities into measurable outcomes, with the opportunity to lead impactful AI initiatives at scale.

Key responsibilities

• Drive large-scale AI/ML programmes, define roadmaps and use Generative AI and LLMs where relevant
• Oversee end-to-end model development, productionisation, integration, monitoring and continuous improvement, with scalability, explainability and governance
• Analyse customer behavioural data for segmentation, propensity modelling, cross-selling, product targeting and lifecycle marketing
• Design and run A/B testing, uplift modelling and other experiments to improve campaign effectiveness
• Mentor data scientists and set best practices for code quality, reproducibility, documentation and model lifecycle management
• Partner with senior business stakeholders and external partners, turning insights into actionable recommendations

Required profile

• Bachelor's or postgraduate degree in Computer Science, Mathematics, Statistics or a related field, with 5-8 years of relevant experience
• Proven technical leadership, problem-solving and stakeholder management skills
• Ability to communicate complex insights clearly to technical and non-technical audiences
• Strong customer-centric mindset and ability to turn data science capabilities into business value

Required skills

• Machine learning and statistical modelling: regression, time-series forecasting, supervised learning, segmentation, clustering, experimentation and causal inference
• Hands-on experience with Generative AI and LLMs, including fine-tuning, evaluation, prompt engineering, red-teaming and performance monitoring
• Python, SQL, Spark, Hadoop/Hive and Databricks; data visualisation with tools such as Power BI
• Version control (GitHub, GitLab, Bitbucket), cloud platforms (AWS, Azure, GCP) and ML lifecycle tools (MLflow, Airflow)