Data scientist

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.
Create labelled hazard-detection datasets covering voids, water ingress, weak zones, utilities, etc.
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:
Data A
Data B
Data C
Data D
Implement early, mid-level, and late fusion strategies.
Estimate anomaly probability scores with confidence intervals.
5. Spatial Analytics & Geospatial Modelling
Convert anomaly scores into geospatial hazard maps.
Use GIS tools (QGIS/Arc GIS) for spatial interpolation and corridor mapping.
Assist in building 1 D/2 D/3 D visualisations for end-users.
6. Technical Reporting & Demonstration
Document all pipelines, algorithms, and findings.
Support the feasibility reporting business case.
ESSENTIAL SKILLS & EXPERIENCE
AI / Machine Learning
Strong expertise in Python (Num Py, Sci Py, Pandas, Py Torch and/or Tensor Flow).
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.
Geospatial / Modelling
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, Gem Py, Oasis Montaj).
Background in geophysics, quantum sensing, or engineering physics.
Knowledge of data fusion techniques and Bayesian modelling.
Experience working with any of:
quantum sensors
inertial navigation
UAV/drone survey data
transport, geotechnical, or civil infrastructure projects