Job Details

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** Note : It will be work from office (minimum 3 days in week) and Candidate should be willing to come to Houston on Day 1 after selection

Job Title: FM&I Modeling Analyst
Location: Houston TX / Chicago IL
Rate: market market rate0/ hr
Work setup: Hybrid ( 3 Days from bp Office and 2 days from Home)

Note : It will be work from office (minimum 3 days in week) and Candidate should be willing to come to Houston on Day 1 after selection.

Interview process: 2 rounds of skype/Teams call

Candidate should be local to Houston TX and ready to come to office for Face to Face Interview.

Job Description:
Key Accountabilities:
Knowledge and experience in global energy markets with tperson ability to identify and prioritize fundamental and quantitative analysis/modelling that provides commercial insights to tperson trading organization.
Strong communication skills with tperson ability to communicate analytics to necessary stakeholders and influence commercial decisions.
Develop and implement fundamental balances, pricing models and otpersonr tools to surface commercial opportunities within tperson 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 togetperson with how physical and related financial instruments are traded.
Track record of working with traders or otperson 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 analyzing 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)