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Optimisation functional sme

Wokingham
Stott & May
Posted: 1 October
Offer description

Overview

Optimisation Functional SME

Start: ASAP
Duration: 6-12 months
Location: Wokingham (3-days on site)
Pay: Inside IR35, up to £425 /day

We are seeking a technically skilled Optimisation & Algorithm Test Engineer to join a high-impact programme within the Electricity System Operator’s Balancing Transformation initiative. This pivotal role supports the development and quality assurance of a modern dispatch optimisation algorithm, working closely with Business Analysts, QA professionals, and Developers to ensure accurate and efficient algorithm functionality.


Responsibilities

* Collaborate with cross-functional teams to support the Dispatch Algorithm development and testing.
* Contribute to the Quality Assurance of optimisation components within the broader Balancing Transformation Programme.
* Review and validate algorithmic test scenarios with business and technical teams.
* Perform exploratory testing and identify defects or irregularities in algorithm performance.
* Assist in developing tools and automating testing processes for optimisation algorithms.
* Work closely with developers and data scientists to refine algorithm outputs and ensure reliability.


Essential Skills & Experience

* Proven experience in solving optimisation problems using a variety of mathematical and computational techniques.
* Familiarity with mathematical programming solvers such as Gurobi for LP, QP, and MIP (MILP, MIQP, MIQCP) problems.
* Strong programming skills in Python and relevant libraries for optimisation and data analysis.
* Solid understanding of data collection, pre-processing, and exploratory data analysis techniques.
* Experience building and deploying custom data models and algorithms to solve real-world problems.
* Experience working with large datasets and drawing actionable insights.
* Strong communication skills to collaborate effectively with business stakeholders and technical teams.
* Experience in QA or software testing environments, ideally within algorithmic or mathematical software contexts.
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