ABOUT AIRSYNQ
AIrSynQ Systems is a TIA-funded, University of the Witwatersrand spin-out developing AI-enabled environmental monitoring and industrial IoT platforms. We operate at the intersection of machine learning, sensor engineering, and real-world African contexts from mine-site air quality to smart industrial sensing based at the Tshimologong Digital Innovation Precinct, Braamfontein.
ROLE OVERVIEW
We are looking for a curious and driven Data Scientist to join a small, research-active team. You will build and deploy machine learning models on time-series IoT sensor data, contribute to peer-reviewed publications, and work closely with engineers and physicists to translate data insights into deployed systems. Wits graduates are strongly encouraged to apply.
KEY RESPONSIBILITIES
• Develop and deploy predictive and anomaly-detection models on environmental and industrial sensor data
• Build end-to-end ML pipelines from raw sensor ingestion to model inference
• Contribute to research outputs, including co-authored journal and conference publications
• Collaborate with hardware and software teams to integrate models into the AIrSynQ platform
• Support data quality assurance and exploratory analysis across new deployment sites
REQUIREMENTS
• BSc, BScHons, or MSc in Data Science, Computer Science, Applied Mathematics, Statistics, Physics, or a related field
• Proficiency in Python and the core ML stack: scikit-learn, TensorFlow or PyTorch, pandas, NumPy
• Exposure to time-series analysis, anomaly detection, or sensor data is advantageous
• Strong analytical thinking and ability to communicate findings clearly
• Ability to work independently in a fast-moving, lean environment