Solutions Manager

About Sand Technologies

Sand Technologies is an international Physical AI company leveraging data and artificial intelligence to enhance the performance of critical sectors. We collaborate globally with governments, cities, and enterprises to optimize essential infrastructure in healthcare, water, energy, telecommunications, and other fields. Our AI solutions have a tangible impact, including managing London's water systems, supporting telecom planning in numerous cities, and providing digital healthcare platforms across Africa. Operating worldwide with teams across Africa, Europe, the UK, and the US, we cover end-to-end AI capabilities from research to deployment and capacity building. Our mission focuses on employing AI to address pressing global challenges.

Role Overview

We are looking for an experienced Senior Data Scientist to join our expanding data science team. This role involves utilizing advanced data analytics and machine learning techniques to solve complex organizational and client challenges, enabling informed decision-making through data-driven solutions. The candidate will bring extensive expertise in statistics, machine learning, and operationalizing data science models at scale.

Key Responsibilities

• Lead independent and collaborative R&D efforts in data science and machine learning to develop innovative models that deliver business value using diverse data sources.
• Enhance and share expertise in decision science, domain and predictive modeling, advanced analytics, MLOps, research, and AI ethics, supporting skill development in colleagues.
• Partner with cross-disciplinary teams to implement machine learning models that are integrated within scalable products and services.
• Clearly communicate findings and their impact to stakeholders of varied technical backgrounds.
• Conduct pioneering research at the intersection of engineering models and AI within Physical AI.
• Guide and mentor junior data scientists to cultivate continuous innovation and learning.

Essential Qualifications and Experience

• Over five years of applied data science experience related to water utilities, wastewater systems, smart infrastructure, or analogous sectors.
• Proven expertise with operational telemetry data, including SCADA, AMI, IoT, and sensor systems.
• Strong background in time-series analysis, anomaly detection, and forecasting tailored to infrastructure systems.
• Experience implementing geospatial analytics and graph/network modeling in practical scenarios.
• Demonstrable success deploying machine learning models into production with proficient handling of data pipelines, MLOps, and ongoing model monitoring.
• Ability to convert advanced analytical insights into actionable guidance for engineering and operations teams.
• Excellent communication capabilities, with experience engaging public-sector or regulated stakeholders.
• Master’s degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative discipline is mandatory; a doctoral degree is favored.

Personal Qualities

• Customer-focused with integrity, upholding values and long-term commitments.
• Collaborative spirit fostering inclusion and mutual knowledge sharing.
• Commitment to operational excellence by simplifying processes and striving for high standards.
• Proactive, accountable with a bias toward action and completing challenging tasks.
• Innovative mindset embracing growth, resilience, and learning from experiences.
• Self-driven and ethical work approach, effectively engaging in virtual collaboration across global teams.