Senior Data Scientist

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Sand Technologies

WebsiteLinkedInAll Job Openings

501 - 1000 employees

🤖 Artificial Intelligence

🏢 Enterprise

☁️ SaaS

Artificial Intelligence • Enterprise • SaaS

Sand Technologies is a global leader in using artificial intelligence and data to address complex problems faced by businesses, industries, and governments worldwide. With a mission to create sustainable solutions beyond the AI hype, Sand Technologies focuses on delivering real value for its customers by solving pressing challenges through innovative digital solutions. The company emphasizes its core values of courage, humility, adventure, initiative, and resilience to drive progress and inspire change. As a team of tech enthusiasts and professionals, Sand Technologies is committed to leveraging AI for good, aiming to make a meaningful difference globally.

📋 Description

• 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

• 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.

🏖️ Benefits

• Health insurance • Paid time off • Professional development • Equipment allowances