Data Scientist

Mirico is an innovative company providing state-of-the-art laser technology solutions for greenhouse gas (GHG) emissions monitoring over large open areas, enabling businesses and industries to achieve their net-zero climate goals. We have demonstrated GHG monitoring solutions in a variety of applications and sites, both domestic and international, across the oil & gas, environmental, agricultural, and public utility sectors over several years. With public interest in GHG reduction and government pledges to reduce GHGs, such as methane by 30% by 2030, the demand for GHG monitoring solutions to protect our climate is now greater than ever.

To meet this rapidly growing demand Mirico is expanding its technology and data analytics, and there is an opportunity for a data scientist to join our talented team of engineers, scientists, and business development staff.

You will play a key role in advancing Mirico’s GHG emissions analytics, helping to develop and refine the pipelines that underpin our insights — including detection, total site quantification, and gas modelling for source localisation and emission estimation. Using your strong analytical and problem-solving skills, you will work with complex real-world datasets from field deployments and apply a combination of Bayesian inference, machine learning, and data-driven modelling techniques to deliver robust, interpretable results.

We are looking for a hands-on, experienced data scientist who can quickly understand our domain, work independently, and bring proven expertise in developing and improving analytical workflows. Working closely with the Mirico team, you will help drive the next stage of our gas-modelling and ML capability, validate and enhance existing algorithms, and translate advanced analytics into actionable insights for customers via the Mirico Insights cloud platform.

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• Analyse and interpret greenhouse gas emissions data from Mirico field deployments
  
• Contribute to the development and enhancement of key analytics pipelines, including:
  
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  • Detection of emission events (signal processing, anomaly detection, ML classification)
    
  • Gas modelling for source localisation and quantification
    
  • Total site quantification of emissions
    
  
  
  
• Research and apply machine learning and AI methods to complement physics-based models, improve detection sensitivity, and automate performance assessment
  
• Take a key role in advancing Mirico’s gas-modelling capability, driving innovation in localisation accuracy and emission estimation
  
• Collaborate with software engineers to integrate and validate analytical models within the Mirico Insights cloud platform
  
• Work with field and business teams to assess site suitability, support deployments, and deliver actionable insights
  
• Produce technical reports and presentations for internal and customer-facing use
  

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• PhD in Data Science, Applied Mathematics, Physics, Engineering, Computer Science or a related quantitative discipline or BSc with >2 years of professional experience as a data scientist
  
• Strong understanding of model development, validation, and deployment in research or production settings
  
• Able to work autonomously, quickly understand new scientific domains, and focus on what matters most analytically
  
• Excels in a collaborative, applied-science environment that values analytical creativity and critical thinking
  
• Strong problem-solving and conceptual reasoning skills; able to diagnose and resolve complex issues logically
  
• Effective time management and ability to prioritise across multiple projects
  
• Experience with scientific software development in Python and associated tools (Git, CI/CD, testing)
  
• Existing right to work in the UK
  
• Experience with machine learning, AI-driven pattern recognition, or anomaly detection in environmental or sensor data
  
• Experience in atmospheric dispersion, Gaussian plume, or advection–diffusion modelling
  
• Knowledge of probabilistic ML or hybrid modelling (combining physics and data-driven approaches)
  
• Familiarity with Bayesian inference, MCMC, or probabilistic programming frameworks (e.g., PyMC, Stan, or TensorFlow Probability)
  
• Operating data science/ML workloads at scale using tools such as Argo Workflows, Prefect or similar
  
• Experience working with geospatial data (e.g., GeoPandas, Shapely, Rasterio)
  
• Knowledge of laser spectroscopy or optical sensing data
  
• Experience developing interactive visualisations or dashboards (e.g., Plotly, Dash, Streamlit)
  
• Willingness to travel within the UK and internationally as required
  

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• Mid-Senior level
  

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• Full-time
  

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• Engineering and Information Technology