Data Scientist (10/01/2025)

Brightsmith
Reading
2 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist (eDV clearance required)

Data Scientist - Remote

Our client is a market leader in renewable energy,from the development, design and construction of large scale solarand BESS installations, to their operation and maintenance andmarket optimisation of BESS assets across the UK and NorthernEurope. To date, the company has constructed over 120 grid-scalesolar farms and 30 energy storage facilities, while its O&Mservice division has 1.6GW of assets under management.Due to theirphenomenal growth, they are seeking a Data Scientist, as part oftheir growing Optimisation team. This role will be responsible fordeveloping the Optimisation back-end systems, undertake complexanalytics, and helping deliver market-leading optimisation strategyfor the companies utility scale battery storage projects. KeyAccountabilities & Responsibilities:Maintain and develop MIROSsoftware for optimisation of battery assets in GBCarry out bespokeanalysis on a variety of subjects involving energy market, as theinternal and external requirements arisesIdentify optimalstrategies for battery storage assets to maintain the team’smarket-leading positionUnderstand the regulatory and policylandscape surrounding the GB energy market in relation tobatteriesBuild and maintain revenue models for the companies growthmarkets Skills & Competencies:Knowledge of the GB electricitymarket, including relevant ancillary services for batteriesSoftwaredevelopment capability (Python)Modelling and data analytics skillsFinancial modellingPython, Excel, SQL, PowerBI, AWS, etc.Strongcommunication skills Personal Characteristics:Ability to workeffectively in a small teamHappy to help set the agenda andadaptable to change depending on the work requirementsAbility tocommunicate across a wide range of stakeholders, including SeniorManagement, employees, and customers. Able to explain complexanalysis to various levels of expertiseExcellent interpersonal andnegotiation skillsWorks well in partnership with internal andexternal key stakeholdersA true team player - fosters teamwork andcollaborationPossesses drive, enthusiasm, andcommitmentQualifications & Experience: Degree in a relevantsubject or equivalent experience in industry

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers

Tips for Staying Inspired: How Machine Learning Pros Fuel Creativity and Innovation

Machine learning (ML) continues to reshape industries—from personalised e-commerce recommendations and autonomous vehicles to advanced healthcare diagnostics and predictive maintenance in manufacturing. Yet behind every revolutionary model lies a challenging and sometimes repetitive process: data cleaning, hyperparameter tuning, infrastructure management, stakeholder communications, and constant performance monitoring. It’s no wonder many ML professionals can experience creative fatigue or get stuck in the daily grind. So, how do machine learning experts keep their spark alive and continually generate fresh ideas? Below, you’ll find ten actionable strategies that successful ML engineers, data scientists, and research scientists use to stay innovative and push boundaries. Whether you’re an experienced practitioner or just breaking into the field, these tips can help you fuel creativity and discover new angles for solving complex problems.

Careers

Top 10 Machine Learning Career Myths Debunked: Key Facts for Aspiring Professionals

Machine learning (ML) has become one of the hottest fields in technology—touching everything from recommendation engines and self-driving cars to language translation and healthcare diagnostics. The immense potential of ML, combined with attractive compensation packages and high-profile success stories, has spurred countless professionals and students to explore this career path. Yet, despite the boom in demand and innovation, machine learning is not exempt from myths and misconceptions. At MachineLearningJobs.co.uk, we’ve had front-row seats to the real-life career journeys and hiring needs in this field. We see, time and again, that outdated assumptions—like needing a PhD from a top university or that ML is purely about deep neural networks—can mislead new entrants and even deter seasoned professionals from making a successful transition. If you’re curious about a career in machine learning or looking to take your existing ML expertise to the next level, this article is for you. Below, we debunk 10 of the most persistent myths about machine learning careers and offer a clear-eyed view of the essential skills, opportunities, and realistic paths forward. By the end, you’ll be better equipped to make informed decisions about your future in this dynamic and rewarding domain.

Careers

Global vs. Local: Comparing the UK Machine Learning Job Market to International Landscapes

How to evaluate opportunities, salaries, and work culture in machine learning across the UK, the US, Europe, and Asia Machine learning (ML) has rapidly transcended the research labs of academia to become a foundational pillar of modern technology. From recommendation engines and autonomous vehicles to fraud detection and personalised healthcare, machine learning techniques are increasingly ubiquitous, transforming how organisations operate. This surge in applications has fuelled an extraordinary global demand for ML professionals—data scientists, ML engineers, research scientists, and more. In this article, we’ll examine how the UK machine learning job market compares to prominent international hubs, including the United States, Europe, and Asia. We’ll explore hiring trends, salary ranges, workplace cultures, and the nuances of remote and overseas roles. Whether you’re a fresh graduate aiming to break into the field, a software engineer with an ML specialisation, or a seasoned professional seeking your next challenge, understanding the global ML landscape is essential for making an informed career move. By the end of this overview, you’ll be equipped with insights into which regions offer the best blend of salaries, work-life balance, and cutting-edge projects—plus practical tips on how to succeed in a domain that’s constantly evolving. Let’s dive in.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.