
Quantum Software - Data Scientist
- Kidlington, Oxfordshire
- Permanent
- Full-time
- Design and implement robust time series models for forecasting, anomaly detection, and predictive maintenance.
- Collaborate with product and engineering teams to integrate predictive models into live quantum sensors.
- Evaluate performance of deployed models and develop tools/pipelines to continuously refine them.
- Analyse large-scale sensor and telemetry data from quantum sensor systems
- Effectively manage technical priorities, meet deadlines, and deliver on project objectives.
- Masters degree in a STEM field (maths, science, engineering etc.) or equivalent
- Strong programming skills in Python (e.g., NumPy, Pandas, scikit-learn, TensorFlow/PyTorch).
- Demonstrable experience in creating and developing Python libraries.
- Demonstrable experience designing, implementing and training machine learning models from scratch.
- Strong foundations in applied mathematics and physics, particularly in statistical modelling, systems dynamics and differential equations.
- Familiarity with software engineering best practices: version control (Git), code review workflows, unit testing, CI/CD pipelines.
- Experience writing clean, efficient, and modular code suitable for production environments.
- Familiarity with AMO physics or quantum machine learning.
- Experience with MLOps best practices.
- Knowledge of systems like Apache Kafka, MQTT or real-time data pipelines.
- Experience with cloud platforms (AWS, Azure, GCP).
- Deep expertise in time series modelling techniques (e.g., ARIMA, VAR, Prophet, LSTM).
- Solid grasp of control theory concepts (e.g., PID controllers, Kalman Filters, Model Predictive Control, Reinforcement Learning).
- Familiarity with lower-level development of data pipelines in e.g. C++/Rust.
- Competitive salary
- Unlimited PTO
- Generous company 10% pension contribution regardless of employee contribution
- Cycle to work scheme
- Tax efficient technology schemes
- Incentive Stock Option Plan
- BUPA Private Healthcare Insurance once probationary period is successfully completed