DATA SCIENTIST / AI SPECIALIST

📢 Hiring: Data Scientist / AI Specialist (7+ Years Experience)

📍 Location:

🕒 Timezone:

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About the Role

Data Scientist / AI Specialist

You will be responsible for building end-to-end data pipelines, implementing ML models, and collaborating closely with scientists and engineers to deliver the core technical outputs.

🔑 Key Responsibilities

1. Data Processing & Signal Analysis

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

2. Simulation & Synthetic Data Development

• Create synthetic datasets using physics-based forward models.
• Add instrument, environmental, and vibration-related noise.
• Build labelled hazard-detection datasets (voids, water ingress, weak zones, utilities, etc.).

3. Machine Learning & Anomaly Detection

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

4. Multi-Sensor Data Fusion

• Develop fusion architectures integrating multiple sensor streams.
• Implement early, mid-level, and late fusion techniques.
• Estimate anomaly probability scores with confidence intervals.

5. Spatial Analytics & Geospatial Modelling

• Convert anomaly outputs into geospatial hazard maps.
• Use GIS tools (QGIS/ArcGIS) for interpolation and corridor mapping.
• Assist with 1D/2D/3D geospatial visualisations.

6. Technical Reporting & Demonstrations

• Document algorithms, pipelines, and findings.
• Support feasibility studies and business-case documentation.

🎯 Essential Skills & Experience

AI / Machine Learning

• Strong Python skills (NumPy, SciPy, Pandas, PyTorch and/or TensorFlow).
• Experience with time-series analysis, anomaly detection, and deep learning.
• Ability to design complete ML pipelines from scratch.

Signal Processing

• Experience with filtering, PSD analysis, spectral methods, Kalman filtering.
• Skilled at working with noisy, multi-sensor real-world datasets.

Geospatial & Modelling

• Experience with spatial data, GIS tools, DEMs, coordinate transforms.
• Exposure to geophysical modelling or physics-driven ML is a plus.

Software Engineering

• Ability to write clean, modular, reproducible scientific code.
• Version control and modular ML pipeline development experience.

Communication

• Strong documentation and technical writing abilities.
• Comfortable collaborating with physicists, engineers, and PMs.

✨ Desirable (Nice-to-Have) Skills

• Experience with gravity/magnetic modelling tools (Fatiando a Terra, GemPy, Oasis Montaj).
• Background in

  geophysics

  ,

  quantum sensing

  , or

  engineering physics

  .
• Knowledge of Bayesian modelling & advanced data fusion.
• Experience with:
• quantum sensors
• inertial navigation systems
• UAV/drone survey datasets
• geotechnical, transport, or civil infrastructure projects