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Senior Data Scientist

Sand Tech Holdings Limited

Salary undisclosed

Remote; South AfricaRemoteadvanced

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Description

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 practical. 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 data science team. As a key contributor, the Senior Data Scientist will be responsible for using their advanced data analysis and machine learning skills to solve complex business problems and drive data-driven decision-making within our organisation and those of our clients. The ideal candidate will have a strong background in statistics, machine learning and data analysis, along with a proven track record of delivering impactful, scalable solutions - with demonstrated experience getting data science solutions into production. Key responsibilities are:

  • Conduct independent (and collaborative) research and development of data science and machine learning models; develop cutting-edge data science and machine learning models that drive business value, leveraging internal and external data sources.
  • You are skilled in, and continue to improve upon your knowledge of decision science, communicating data, domain modelling, predictive modelling, advanced analytics, MLOps, Research and AI Ethics with the willingness to up skill others in these competencies.
  • Collaborate with cross-functional teams: work closely with cross-functional teams to apply data science and machine learning models to business problems, ensuring that models are integrated into scalable products and services.
  • Communicate results and impact: communicate results and impact to stakeholders, including technical and non-technical audiences.
  • Perform cutting edge research in Physical AI, at the intersection of engineering models and AI.
  • Mentor junior data scientists: mentor junior data scientists, fostering a culture of continuous improvement and innovation.

 

Requirements - Essential

  • 5+ years of applied data science experience in water, wastewater, utilities, or smart infrastructure environments.
  • Demonstrated experience working with operational telemetry data (SCADA, AMI, IoT, sensor systems).
  • Strong expertise in time-series modeling, anomaly detection, and forecasting for infrastructure systems.
  • Experience applying geospatial analytics and/or graph/network modeling in real-world systems.
  • Proven track record of deploying ML solutions into production, including data pipelines, MLOps, and model monitoring.
  • Ability to translate advanced analytics into actionable insights for engineering and operations teams.
  • Strong communication skills and experience working with public-sector or regulated environments.
  • M.Sc. (Master’s degree) in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field required; PhD preferred.

Personal Attributes

  • Client Centricity & Integrity: We let Our Clients Run the Company, Surf Like Yvon Chouinard to stay true to our values, and Play the Long Game with integrity.
  • Collaboration and Inclusion: We live by Each One, Teach Ten and ensure Everybody is Welcome.
  • Operational Excellence and Simplicity: We K.I.S.S. by keeping things simple while always striving to Raise the Bar.
  • Action, Ownership, and Execution: We Decide, Get Stuff Done, and Do Hard Things with accountability.
  • Growth, Innovation, and Resilience: We Choose Growth, Pioneer boldly, and remember There is No Failure.

Due to the considerable amount of virtual work and interaction with colleagues and customers in different physical locations internationally, it is essential that the successful applicant has the drive and ethics to succeed in working in small teams physically but in larger efforts virtually. Self-drive to communicate constantly using web collaboration and video conferencing is essential.

 

About this role

Sand Technologies is looking for a Senior Data Scientist to work on AI systems that solve real infrastructure challenges—water management, energy, telecommunications, and healthcare across Africa and beyond. This remote role is based in South Africa and sits within a team that bridges research, engineering, and on-the-ground deployment.

You'll lead independent and collaborative research to build machine learning models that move from prototype to production, with a particular focus on Physical AI at the intersection of engineering models and data. The work centers on operational telemetry from infrastructure systems—SCADA, IoT sensors, AMI data—requiring deep expertise in time-series forecasting, anomaly detection, and geospatial or network modeling. You'll translate complex analytics into actionable insights for engineering and operations teams, collaborate across functions to integrate models into scalable products, and mentor junior data scientists. This demands both technical rigor and the ability to communicate findings clearly to non-technical stakeholders in public-sector and regulated environments.

The ideal candidate brings 5+ years of applied data science in water, utilities, or smart infrastructure, with proven success shipping ML solutions into production—including data pipelines, MLOps, and monitoring. A Master's degree in Data Science, Statistics, Mathematics, Computer Science, or related field is required; a PhD is preferred. Beyond credentials, you'll need the self-drive to work effectively across distributed teams, strong communication discipline in virtual settings, and the integrity and ownership mindset that Sand values in its people.

Pay for this role

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