Senior Data Scientist

About Sand

Sand Technologies is a global Physical AI company using data and AI to make critical industries work better. We partner with governments, cities and enterprises to improve how essential systems operate across healthcare, water, energy, telecommunications and infrastructure.

Our work delivers proven real-world impact. We have built AI systems that help manage London’s water supply, supported telecom network planning across hundreds of cities, and developed digital healthcare platforms serving tens of millions of people across Africa. From intelligent command centers to AI-powered infrastructure platforms, we help organizations sense, analyze and act in complex environments.

Our people are ambitious, curious and relentlessly seek impact. Our teams work alongside clients in the field, solving hard problems and deploying solutions that last. With colleagues across Africa, Europe, the UK and the US, we operate across the full stack - from research and engineering to deployment and capability building.

Our mission is simple: to harness AI to solve humanity’s most pressing challenges.

About the role

We are seeking an experienced Senior Data Scientist to join our growing Utilities domain team. As a key contributor, the Senior Data Scientist will be responsible for leveraging their advanced data analysis and machine learning skills to solve complex business problems and drive data-driven decision-making within our organization and those of our utility clients (focusing on areas such as grid optimization, asset management, and consumption forecasting).

The ideal candidate will have a strong background in statistics, machine learning, and data analysis, along with a proven track record of delivering impactful insights and solutions, with demonstrated experience delivering valuable outcomes through data science.

What you’ll do

• Model Research & Development: Conduct independent and collaborative research and development of data science and machine learning models; develop cutting-edge models that drive business value for the utility sector, using internal and external data sources to deliver intelligence.
• Continuous Capability Growth: Maintain and improve your knowledge of decision science, communicating data, domain modeling, predictive modeling, advanced analytics, MLOps, Research, and AI Ethics, with the willingness to upskill others in these competencies.
• Collaborate Cross-Functionally: Work closely with cross-functional teams to apply data science and machine learning models to utility business problems, ensuring that models are integrated into production products and services.
• Communicate Results & Impact: Effectively communicate results and impact to stakeholders, including both technical and non-technical audiences.
• Stay Current with Industry Developments: Keep up to date with developments across data science and machine learning, identifying opportunities for applied research and development.
• Mentor Junior Talent: Mentor junior data scientists within the domain, fostering a culture of continuous improvement and innovation.

Who you are

• 4+ years of experience in data science and machine learning, with a strong track record of independent research and development.
• Prior experience in the Utilities domain is advantageous (e.g., smart grids, resource forecasting, IoT, or energy analytics).
• Fluency in Python with experience with at least one cloud provider; preferably Azure.
• Qualified experience in a related field, including, but not limited to, Data Science, Machine Learning, Computer Science, or Statistics.
• Strong experience in delivery across the lifecycle of machine learning products, adhering to robust software engineering practices.
• Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and translate complex data concepts into actionable business insights.

How we work

Due to the highly collaborative and internationally distributed nature of our work, successful candidates must be comfortable operating in small teams while contributing to larger, globally coordinated efforts. A strong sense of ownership, self-motivation and discipline in maintaining clear and consistent communication through virtual collaboration tools and video conferencing is essential.