Data Scientist & AI Specialist

Entergaia Technologies UK Limited; United Kingdom; On-site; GBP 50,000 - 70,000; Full time

Job summary

A cutting-edge energy technology firm in the UK is seeking a Data Scientist / AI Specialist to develop advanced analytics and machine learning models for their gravimetry and magnetometry project. In this role, you will process sensor data, develop anomaly detection algorithms, and work closely with scientific teams. The ideal candidate has strong expertise in Python, time-series modelling, and signal processing, making this a unique opportunity in a sustainable energy context.

Qualifications

• Strong expertise in Python and experience with time-series modelling.
• Ability to work with noisy multi-sensor measurement data.
• Experience in designing ML pipelines from scratch.

Responsibilities

• Process raw gravity, magnetic, IMU, and GNSS sensor data.
• Generate synthetic datasets from physics-based models.
• Design, train, and evaluate machine learning models.

Skills

Python (NumPy, SciPy, Pandas, PyTorch, TensorFlow)

Time-series modelling

Anomaly detection

Deep learning architectures

Signal processing

GIS tools (QGIS/ArcGIS)

Tools

PyTorch

TensorFlow

Git

Job description

Entergaia Technologies, headquartered in Aberdeen, UK, is a pioneering company specializing in innovative wireless power transfer and smart energy storage solutions. With a strong emphasis on sustainability and efficiency, Entergaia is revolutionizing energy transmission.

Job Specification (Initial Three Months & Extendable to 18 months)

We are seeking a highly capable Data Scientist / AI Specialist to lead the development of advanced analytics and machine-learning techniques for our gravimetry and magnetometry project. This is a unique opportunity to work at the cutting edge of artificial intelligence—developing algorithms that detect anomalies.

You will design and build the full data pipeline, working directly with other scientists and engineers to deliver the core technical output.

KEY RESPONSIBILITIES

1. Data Processing & Signal Analysis

• Process raw gravity, magnetic, IMU, and GNSS sensor data.
• Develop filtering, denoising, drift correction, vibration correction, and resampling pipelines.
• Convert time-series sensor outputs into calibrated spatial anomaly profiles.

2. Simulation & Synthetic Data Development

• Generate synthetic datasets from physics-based forward models.
• Add realistic noise (instrument, environmental, vibration) to training data.

3. Machine Learning & Anomaly Detection

• Design, train, and evaluate models for:
• anomaly detection
• classification of subsurface hazards
• uncertainty quantification
• Use classical ML (Random Forest, XGBoost, SVM) and deep learning (CNNs, LSTMs, autoencoders, transformers).
• Develop semi-supervised and unsupervised models for scarce labelled data.

4. Multi-Sensor Data Fusion

• Build fusion architectures that combine sensor datasets
• Implement early, mid-level, and late fusion strategies.
• Estimate anomaly probability scores with confidence intervals.
• Convert anomaly scores into geospatial hazard maps.
• Use GIS tools (QGIS/ArcGIS) for spatial interpolation and corridor mapping.
• Assist in building 1D/2D/3D visualisations for end-users.

6. Technical Reporting & Demonstration

• Document all pipelines, algorithms, and findings.
• Support feasibility reporting business case.

ESSENTIAL SKILLS & EXPERIENCE

• Strong expertise in Python (NumPy, SciPy, Pandas, PyTorch and/or TensorFlow).
• Experience with time-series modelling, anomaly detection, and deep learning architectures.
• Experience designing ML pipelines from scratch.

Signal Processing

• Proficiency in filtering, PSD analysis, spectral methods, and Kalman filtering.
• Experience handling noisy, multi-sensor, real-world measurement data.
• Ability to work with spatial data (GIS, coordinate transforms, DEMs).
• Experience with geophysical modelling or physical-simulation-driven ML (advantage).

Software Engineering

• Ability to write clean, reproducible, version-controlled scientific code.
• Experience building modular ML pipelines.

Communication

• Ability to write technical documentation clearly.
• Comfortable working with physicists, engineers, and project managers.

DESIRABLE SKILLS (Nice to Have)

• Experience with gravity/magnetic modelling (Fatiando a Terra, GemPy, Oasis Montaj).
• Background in geophysics, quantum sensing, or engineering physics.
• Knowledge of data fusion techniques and Bayesian modelling.
• Experience working with any of:
• inertial navigation
• transport, geotechnical, or civil infrastructure projects

HOW TO APPLY

Please send:

• CV
• examples of relevant projects or GitHub/portfolio