

IT WORLD LIMITED
FM&I Modeling Analyst
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an FM&I Modeling Analyst with a contract length of "unknown," offering a pay rate of "unknown." Candidates should have experience in European energy markets, strong analytical skills, and proficiency in Python for modeling and data analysis.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
-
💰 - Day rate
Unknown
-
🗓️ - Date
December 9, 2025
🕒 - Duration
Unknown
-
🏝️ - Location
Unknown
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
London Area, United Kingdom
-
🧠 - Skills detailed
#Data Pipeline #Libraries #Data Engineering #Regression #Datasets #Python #Time Series #Data Science #ML (Machine Learning) #Pandas #NumPy
Role description
Role: FM&I Modeling Analyst
Key Accountabilities:
Knowledge and experience in global energy markets with the ability to identify and prioritize
fundamental and quantitative analysis/modelling that provides commercial insights to the trading
organization.
Strong communication skills with the ability to communicate analytics to necessary stakeholders and
influence commercial decisions.
Develop and implement fundamental balances, pricing models and other tools to surface commercial
opportunities within the low-carbon, power, gas, and oil markets, harnessing best practices and advanced
modelling techniques.
Engage with stakeholders (traders and analysts) to ensure that solutions/models are optimal and deliver
deep commercial insight.
Identify repetitive processes that can be standardized into modules that can be reused across projects.
Essential Experience
Undergraduate degree in STEM subject or quantitative discipline.
Knowledge of European energy markets (e.g. gas, LNG, or power).
Understanding of supply and demand drivers together with how physical and related financial
instruments are traded.
Track record of working with traders or other business stakeholders to create commercially actionable
models.
Experience with a range of modelling techniques including, regression, time series analysis, forecast
modelling and machine learning.
Excellent problem-solving skills.
Experience using a coding language to develop models and analytical tools.
Experience manipulating and analysing large, complex datasets.
Desirable Experience & Skills
Practical knowledge of data engineering practices (designing and building robust data pipelines)
Knowledge of python and core libraries applicable to data science (e.g., pandas, numpy, statsmodel)
Role: FM&I Modeling Analyst
Key Accountabilities:
Knowledge and experience in global energy markets with the ability to identify and prioritize
fundamental and quantitative analysis/modelling that provides commercial insights to the trading
organization.
Strong communication skills with the ability to communicate analytics to necessary stakeholders and
influence commercial decisions.
Develop and implement fundamental balances, pricing models and other tools to surface commercial
opportunities within the low-carbon, power, gas, and oil markets, harnessing best practices and advanced
modelling techniques.
Engage with stakeholders (traders and analysts) to ensure that solutions/models are optimal and deliver
deep commercial insight.
Identify repetitive processes that can be standardized into modules that can be reused across projects.
Essential Experience
Undergraduate degree in STEM subject or quantitative discipline.
Knowledge of European energy markets (e.g. gas, LNG, or power).
Understanding of supply and demand drivers together with how physical and related financial
instruments are traded.
Track record of working with traders or other business stakeholders to create commercially actionable
models.
Experience with a range of modelling techniques including, regression, time series analysis, forecast
modelling and machine learning.
Excellent problem-solving skills.
Experience using a coding language to develop models and analytical tools.
Experience manipulating and analysing large, complex datasets.
Desirable Experience & Skills
Practical knowledge of data engineering practices (designing and building robust data pipelines)
Knowledge of python and core libraries applicable to data science (e.g., pandas, numpy, statsmodel)






