Data Scientist
Data Scientist builds and deploys AI models for infrastructure systems, focusing on utilities and smart cities, using time-series, geospatial, and MLOps techniques.
- Compensation
- Not disclosed
- Location
- Baltimore, United States
- Work setup
- Onsite
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Data science
- Posted
Skills
Must have
- 3+ 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.
Full 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 Data Scientist to join our growing data science team. As a key contributor, the 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.