Aligne Technologies Ltd is a leading consultancy specializing in delivering innovative business and technical solutions across finance, telecoms, and energy sectors. Founded in 2014, our team of seasoned professionals is committed to excellence and building strong client relationships. We partner with global technology leaders such as IBM, Google, and Infosys to provide specialized expertise on a worldwide scale.
Summary
Role Purpose
To develop, implement, and maintain
fundamental and quantitative models
that provide deep commercial insights and actionable trading strategies across global low-carbon, power, gas, and oil markets. This role is pivotal in translating complex market dynamics into competitive advantage for the trading organization.
Key Accountabilities (What you'll be doing)
Commercial Modeling:
Design, build, and deploy robust fundamental balances, pricing models, and analytical tools to pinpoint
commercial opportunities
in the low-carbon, power, gas, and oil sectors.
Strategic Insight:
Leverage knowledge of
global energy markets
to prioritize and execute modeling and analysis that yields critical insights for trading decisions.
Stakeholder Engagement:
Actively collaborate with traders and analysts to ensure modeling solutions are
optimal, commercially actionable
, and fully address business needs.
Communication & Influence:
Effectively communicate complex analytical findings and model results to necessary stakeholders, using data to
influence key commercial decisions
.
Process Efficiency:
Identify and standardize repetitive analytical processes, developing
reusable modules
to enhance modeling efficiency and consistency across projects.
Essential Experience & Qualifications (The Non-Negotiables)
Education:
Undergraduate degree (or equivalent) in a
STEM
subject or a quantitative discipline.
Market Knowledge:
Demonstrated knowledge of
European energy markets
(e.g., natural gas, LNG, or power).
Trading Mechanics:
Solid understanding of
supply and demand drivers
and the trading mechanics of both physical and related financial energy instruments.
Applied Modeling:
A proven track record of successfully collaborating with traders or business stakeholders to build
commercially actionable models
.
Techniques:
Hands-on experience with a diverse range of
modeling techniques
, including but not limited to regression, time series analysis, forecasting, and machine learning.
Technical Skills:
Proficiency in using a
coding language
(e.g., Python, R, MATLAB) to develop models and analytical tools.
Data Proficiency:
Experience in
manipulating and analyzing large, complex datasets
.
Problem-Solving:
Excellent, demonstrable
problem-solving skills
.
Desirable Experience & Skills (The Bonus Points)
Programming/Data Science:
Practical knowledge of
Python
and its core data science libraries (e.g., pandas, numpy, statsmodels, scikit-learn).
Data Engineering:
Practical knowledge of data engineering best practices, including designing and building