Data Scientist

Join a team that brings together advanced data engineering and the latest breakthroughs in artificial intelligence. At Insights & Data, we build scalable Cloud, Big Data, and Generative AI solutions that transform how organizations work with information. As a Senior Data Scientist you will shape the technological direction of key projects, collaborate with experts in our AI Center of Excellence and design architectures that define the future of intelligent systems. This role combines advanced technical expertise in data science with consulting skills to provide strategic guidance and solutions to clients.

• Proven track record of delivering AI systems in production, covering the full development lifecycle.
• Deep understanding of Machine Learning, Generative AI, and agentic AI architectures, including modern approaches to intelligent system design.
• Hands-on experience with at least two major cloud platforms: GCP, AWS, or Microsoft Azure.
• Strong Python combined with a production grade engineering mindset and clean coding practices.
• Experience with CI/CD pipelines and modern MLOps practices, including automation, monitoring, and model deployment.
• Familiarity with modern data platforms, such as Databricks or Snowflake.
• Experience leading teams or technical workstreams in AI or data-focused projects.
• Very good stakeholder communication and decision-making skills, with the ability to collaborate with both technical and business audiences.

• Own the full lifecycle of data and AI projects — from discovery and problem framing, through modeling and validation, to deployment and delivery.
• Apply a wide range of techniques, including statistics, machine learning, forecasting, optimization, and Generative AI where appropriate.
• Design and deliver production ready solutions, going beyond prototypes and ensuring long-term maintainability and scalability.
• Collaborate directly with clients, leading scoping sessions, workshops, and translating ambiguous requirements into clear, actionable deliverables.
• Balance rigor with pragmatism by selecting the right level of analytical and technical sophistication for each problem.
• Communicate insights effectively to both technical and nontechnical stakeholders, adapting style and depth to the audience.