33 Commercial Modelling Analyst 87388 jobs in the United Kingdom

• Develop and implement remote sensing data acquisition and processing strategies.
• Analyze satellite, aerial, and drone imagery for crop health, stress, and yield assessment.
• Utilize GIS software and techniques to manage and interpret spatial data.
• Develop and apply statistical and machine learning models for agricultural data analysis.
• Provide expert agronomic advice based on data-driven insights.
• Collaborate with R&D teams to develop new analytical tools and methodologies.
• Present findings and recommendations to clients and stakeholders.
• Stay abreast of advancements in remote sensing technologies and agricultural data science.
• Ensure data quality, integrity, and security throughout the analysis process.
• Contribute to the development of data-driven products and services.

• Master's or PhD in Agronomy, Crop Science, Soil Science, Geospatial Science, or a related agricultural field.
• Minimum of 5 years of experience in agronomy, with a focus on remote sensing and data analysis.
• Proficiency in GIS software (e.g., ArcGIS, QGIS) and remote sensing platforms (e.g., Google Earth Engine, ERDAS Imagine).
• Strong programming skills in R, Python, or similar languages for data analysis.
• Experience with agricultural data formats and platforms.
• Excellent understanding of crop physiology, soil science, and agricultural management practices.
• Strong analytical, problem-solving, and critical-thinking skills.
• Excellent written and verbal communication skills.
• Ability to work independently and manage projects effectively in a remote environment.

• Analyze satellite and aerial imagery using remote sensing techniques to monitor crop health and growth.
• Process and interpret geospatial data for precision agriculture applications.
• Develop and validate models for predicting crop yields and identifying disease or pest outbreaks.
• Utilize GIS software and data analysis tools (R, Python) to extract insights from agricultural data.
• Collaborate with agronomists and farmers to provide data-driven recommendations for crop management.
• Contribute to the development of data-driven agricultural management platforms.
• Evaluate new technologies and methodologies in remote sensing and precision agriculture.
• Prepare technical reports and presentations on findings and recommendations.
• Ensure data quality and integrity throughout the analysis process.
• Support the implementation of data-driven solutions on farms.

• Master's or Ph.D. in Agronomy, Soil Science, Remote Sensing, Geography, or a related field.
• Proven experience in analyzing agricultural data using remote sensing and GIS tools.
• Strong proficiency in statistical analysis and programming languages such as R or Python.
• Familiarity with drone-based data acquisition and processing is a plus.
• Knowledge of different crop types and agricultural practices.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and reporting skills, with the ability to explain complex data to non-technical audiences.
• Ability to work independently and manage multiple projects in a remote environment.
• Experience with machine learning techniques applied to agriculture is advantageous.

• Manage, process, and interpret large geological, geophysical, and geochemical datasets.
• Utilize advanced software for 3D geological modeling, spatial analysis, and data visualization.
• Develop and refine exploration models and targeting strategies based on data analysis.
• Collaborate closely with remote geologists, geophysicists, and geochemists to integrate diverse data streams.
• Contribute to the planning and design of exploration programs, including drill campaigns and field data acquisition.
• Prepare technical reports, presentations, and geological summaries for internal and external stakeholders.
• Conduct peer reviews of geological interpretations and data quality.
• Mentor junior geologists in data analysis techniques and geological interpretation.
• Stay current with emerging exploration technologies and methodologies.
• Ensure adherence to best practices in data management and geological reporting.

• Master's or PhD in Geology, Geophysics, or related field.
• 8+ years of experience in mineral exploration and data analysis.
• Expertise in geological software (e.g., Leapfrog, ArcGIS, Oasis Montaj).
• Strong understanding of geostatistics and spatial data analysis.
• Proven ability to interpret geophysical and geochemical data.
• Excellent analytical, problem-solving, and report-writing skills.
• Demonstrated ability to work independently in a remote environment.

Drive the Future of Formula 1 with GM PPU!
Increase your chances of an interview by reading the following overview of this role before making an application.
At GM Performance Power Units (GM PPU), we're driving innovation in Formula 1 Energy Recovery Systems (ERS). As an ERS Performance & Data Analysis Engineer, you'll optimize ERS performance and extract valuable insights from data to propel our success on the track.
Key Responsibilities:
• Analyze ERS performance data to identify areas for improvement and implement enhancements
• Develop and maintain data pipelines for efficient collection and processing of ERS performance metrics
• Create data models and visualization tools to present complex ERS performance data in an accessible format
• Collaborate with cross-functional teams to integrate performance insights into the development process of ERS components
• Monitor and evaluate ERS performance during testing and race events, providing real-time analysis and recommendations
• Develop algorithms and statistical models to predict ERS performance under various conditions
• Ensure compliance with FIA regulations regarding energy deployment and recovery.

Qualifications:
• Bachelor's degree in Electrical Engineering, Mechanical Engineering, or related field with 5+ years of relevant experience in motorsports industry, OR
• Master's degree in Electrical Engineering, Mechanical Engineering, or related field with 1+ years of relevant experience
• Demonstrated experience with data analysis and performance optimization in high-performance engineering environments

Desirable Skills:
• Strong understanding of Formula 1 and motorsport regulations, particularly those related to Energy Recovery Systems (ERS)
• Proficiency in data analysis tools and programming languages such as Python, R, or MATLAB
• Experience with data visualization tools like Tableau or Power BI
• Knowledge of statistical analysis and machine learning techniques
• Familiarity with data pipeline architectures and ETL processes
• Strong analytical and problem-solving skills
• Experience with Formula 1 or high-performance motorsport ERS systems
• Knowledge of real-time data acquisition systems used in motorsports
• Familiarity with cloud-based data processing platforms
• Understanding of aerodynamics and its impact on ERS performance
Personal Attributes:
• Experience with Formula 1 or high-performance motorsport ERS systems
• Knowledge of real-time data acquisition systems used in motorsports
• Familiarity with cloud-based data processing platforms
• Understanding of aerodynamics and its impact on ERS performance

Drive the Future of Motorsport with GM PPU!
At GM PPU, we’re not just building power units — we’re shaping the future of Formula 1 technology. Our culture of collaboration fuels creativity and innovation, empowering you to make a real impact on the track. Every idea counts, every breakthrough matters, and every team member contributes to our competitive edge.

If you’re passionate about revolutionizing electric powertrain technology and ready to help us push the limits of performance, this is your chance to join a high-energy, cutting-edge team on a mission to dominate the grid. Your journey to F1 starts here! Apply today and become part of something extraordinary.

GM Performance Power Units and all affiliated companies are Equal Opportunity employer(s). Minorities, women, veterans, and individuals with disabilities are encouraged to apply. For more information regarding the EEOC, please visit

Only direct hires need apply to or inquire about job postings at GM Performance Power Units. We are not accepting calls, resumes or applications from recruiting firms at this time.

The Administrative Support Officer provides essential support to ensure efficient office operations and assists various departments by managing administrative tasks, coordinating communication, and maintaining organizational systems. This role is vital in fostering a productive and organized work environment.

Key Responsibilities

• Manage day-to-day office activities including scheduling, correspondence, and filing.
• Handle incoming calls, emails, and visitor inquiries professionally and promptly.
• Prepare and process documents, reports, and presentations as required.
• Maintain office supplies inventory and coordinate procurement when necessary.
• Assist in organizing meetings, events, and travel arrangements.
• Support HR and finance departments with data entry and record-keeping tasks.
• Ensure office equipment is functioning and arrange for repairs when needed.
• Maintain accurate and confidential records and databases.

Qualifications & Skills

• High school diploma or equivalent; relevant certifications or diploma in office administration is an advantage.
• Proven experience in administrative or office support roles.
• Excellent organizational and multitasking skills.
• Strong communication and interpersonal abilities.
• Proficiency in Microsoft Office Suite (Word, Excel, Outlook).
• Ability to handle sensitive information with discretion.
• Detail-oriented with good problem-solving skills.

• Developing and implementing complex quantitative models for derivative pricing, risk management, and portfolio optimization.
• Conducting rigorous model validation and back-testing to ensure accuracy and reliability.
• Programming in languages such as Python, C++, or R for model development and implementation.
• Collaborating with traders, risk managers, and portfolio managers to understand their needs and provide quantitative solutions.
• Contributing to the research and development of new pricing methodologies and risk measures.
• Monitoring and analyzing market data to identify trends and opportunities.
• Ensuring compliance with regulatory requirements and internal policies.
• Documenting model specifications, methodologies, and assumptions thoroughly.
• Communicating complex quantitative concepts clearly to both technical and non-technical stakeholders.
• Mentoring junior quantitative analysts and sharing knowledge within the team.
• Assisting in the implementation of new trading systems and risk platforms.
• Performing ad-hoc analysis and research as required by senior management.

• Develop, implement, and validate sophisticated quantitative models for financial markets.
• Design and implement algorithms for pricing, risk management, and trading strategies.
• Utilize statistical modeling, machine learning, and econometrics to analyze financial data.
• Perform rigorous back-testing, stress-testing, and sensitivity analysis of models.
• Collaborate with business stakeholders to understand requirements and deliver data-driven solutions.
• Communicate complex quantitative findings to technical and non-technical audiences.
• Ensure model compliance with regulatory requirements and internal policies.
• Contribute to the continuous improvement of quantitative methodologies and infrastructure.

• Master's or PhD in Finance, Mathematics, Statistics, Physics, Computer Science, or a related quantitative field.
• Minimum of 5 years of relevant experience in quantitative analysis within the financial services industry.
• Proven expertise in financial modeling, risk management, and/or algorithmic trading.
• Proficiency in programming languages such as Python, R, C++, or MATLAB.
• Strong knowledge of financial markets, derivatives, and econometrics.
• Excellent analytical, problem-solving, and critical thinking skills.
• Effective communication and presentation skills.
• Ability to work effectively in a hybrid team environment.