Senior Data Scientist

Titles? Meh. We’re not obsessed with them! Internally, you’ll be a Data Scientist like the rest of the team 😉

Just with that extra layer of expertise, strategic mindset, and the ability to build solutions that truly move the needle. We’re expanding our Data & Analytics team with a senior professional who can lead complex initiatives, influence architecture and methodology, and help shape data-driven decision-making across the organization. If you thrive at the intersection of technical depth, business understanding, and hands-on problem-solving, you’ll fit right in.

What You Will Be Doing

• Identify, qualify, and shape opportunities for Data Science projects across different industries.
• Design and deliver end-to-end data solutions: from exploration and modelling to deployment and validation.
• Lead client engagements from initial discussions through project scoping, planning, and proposal development.
• Build, evaluate and refine statistical models, predictive algorithms, and data-driven decision systems.
• Collaborate closely with engineering teams to ensure smooth deployment, scalability, and monitoring.
• Guide best practices in data quality, modelling standards, and reproducibility.
• Mentor team members and contribute to continuous learning across the organization.
• Support commercial efforts by shaping technical approaches, contributing to proposals, and helping close deals.
• Develop long-term relationships with clients and stakeholders.

Requirements

• 5+ years of experience in Data Science, Machine Learning, or Advanced Analytics.
• Proven experience shaping and closing data-driven or technical project opportunities.
• Strong understanding of statistical modelling, predictive analytics, and business problem-solving.
• Excellent communication skills — able to translate complex insights into actionable recommendations.
• Demonstrated ability to build and deliver data products or analytical solutions end-to-end.
• Solid experience with Python (expert level) and strong SQL skills.
• Hands-on experience with common DS libraries (pandas, NumPy, scikit-learn, PyTorch/TensorFlow, etc.).
• Comfortable working with cloud or modern data platforms.
• Fluent English (mandatory).

Nice to have

• Experience with Big Data ecosystems or cloud platforms (Azure, AWS, GCP).
• Experience deploying models in production or working with MLOps concepts.
• Knowledge of NLP, Computer Vision, time series, or recommendation systems.
• Experience with API development, CI/CD, or containerization.
• Strong software engineering fundamentals (testing, versioning, code structure).
• Experience with dashboarding or BI tools (Power BI, Looker, Tableau).
• Familiarity with data architectures, ETL/ELT pipelines, or data engineering concepts.