Description

We're looking for an experienced senior data scientist to design and deliver data-driven solutions that solve complex business problems and create measurable impact.

Working closely with business stakeholders, product teams, and technical experts, you'll transform business challenges into scalable analytical, machine learning, and GenAI solutions. From defining use cases to deploying production-ready models, you'll play a key role in delivering innovative AI solutions that drive better decision-making and customer outcomes.

Requirements

What you'll do

• Collaborate with business stakeholders to identify and prioritize AI and analytics opportunities
• Translate business requirements into scalable data science and machine learning solutions
• Validate data availability and define analytical approaches for new use cases
• Build predictive models, machine learning solutions, and GenAI applications
• Design robust data pipelines and analytical workflows
• Apply data processing, feature engineering, and statistical modelling techniques
• Ensure solutions are scalable, production-ready, and aligned with software engineering and MLOps best practices
• Present analytical findings and recommendations to technical and executive stakeholders
• Communicate AI capabilities, feasibility, risks, and expected business value in a clear and practical way
• Mentor junior team members and support technical delivery across multiple initiatives

You're our match if you have

• Master's degree in data science, computer science, artificial intelligence, mathematics, software engineering, or a related field
• 5+ years of hands-on experience delivering data science or machine learning solutions
• Strong Python programming skills and experience with modern data science libraries
• Experience building predictive models, machine learning solutions, and GenAI applications
• Strong understanding of statistics, data modelling, and feature engineering
• Experience designing scalable data pipelines and production-ready AI solutions
• Familiarity with MLOps, model deployment, and machine learning lifecycle management
• Excellent stakeholder management and communication skills
• Ability to translate complex technical concepts into business value

Bonus points if you have experience with

• Telecommunications or other customer-centric industries
• Large-scale customer analytics and segmentation
• Large language models (LLMs) and retrieval-augmented generation (RAG)
• Cloud platforms such as Azure, AWS, or Google Cloud
• Databricks, Spark, or distributed data processing
• Docker, Kubernetes, or CI/CD pipelines
• Leading or mentoring technical teams