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- Tasks: Develop analytical models and dashboards to support market analysis and commercial strategy.
- Company: Join a leading firm in market and performance analytics.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and career advancement.
- Why this job: Make a real impact by translating data into actionable insights for strategic decisions.
- Qualifications: Experience in data science, strong Python skills, and a knack for clear communication.
The predicted salary is between 50000 - 70000 £ per year.
We are seeking a Data Scientist to strengthen our client’s market and performance analytics capability, supporting commercial strategy and policy decisions across trading and asset operations. The role focuses on extracting insight from market data and asset performance, combining statistical analysis, machine learning, and domain understanding to inform high-impact commercial decisions.
You will work closely with Commercial, Trading, and Analytics teams, translating complex data into clear, decision-ready insight. The role sits at the interface between quantitative analysis and commercial application, complementing optimisation and trading-focused analytics with deeper explanatory and diagnostic capability.
Responsibilities- Develop and maintain analytical models and dashboards supporting market analysis across wholesale and ancillary services markets; asset performance, value capture, and post-event attribution; and commercial strategy, pricing signals, and policy decision support.
- Apply statistical and machine learning techniques to identify drivers of market behaviour, performance variance, and structural change. Conduct deep-dive analyses on spreads, volatility, regime shifts, and asset utilisation to support strategic and tactical decisions.
- Translate analytical outputs into clear narratives and recommendations for Commercial and senior stakeholders.
- Partner with Trading, Asset Management, and Optimisation teams to ensure consistency of assumptions, data, and interpretation across analytical outputs.
- Contribute to the development of reusable analytics, datasets, and performance metrics within the wider analytics platform.
- Support ad-hoc commercial and policy-driven analysis with rapid, high-quality quantitative insight.
- Strong professional experience as a data scientist or quantitative analyst in a data-intensive environment.
- Advanced Python skills for data analysis, including data manipulation and feature engineering, statistical modelling and machine learning, and clear, reproducible analytical workflows.
- Solid grounding in statistics and applied analytics, including uncertainty, attribution, and performance analysis.
- Experience working with time series data and large, complex real-world datasets.
- Ability to communicate complex quantitative findings clearly to non-technical stakeholders.
- Experience or interest in energy markets, commodities, or infrastructure-heavy industries.
- Familiarity with power market fundamentals, asset economics, or trading-driven performance metrics.
- Experience with modern data stacks, analytical databases, or visualisation tools.
- Exposure to optimisation, forecasting, or simulation models, even if not a primary developer. Comfort operating at the intersection of analytics, commercial decision-making, and policy considerations.
- Commercially minded, with a strong instinct for what analysis matters in decision-making.
- Analytically rigorous but pragmatic, balancing precision with timeliness.
- Comfortable working across teams and influencing decisions through insight rather than authority.
- Motivated by applying data science to real-world systems with material financial and operational impact.
Data Scientist employer: Mint Selection | B Corp
Contact Detail:
Mint Selection | B Corp Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or conferences related to data science. You never know who might have a lead on your dream job or can introduce you to someone at a company you're eyeing.
✨Show Off Your Skills
Create a portfolio showcasing your projects and analyses. Use platforms like GitHub to share your code and visualisations. This not only demonstrates your technical skills but also your ability to communicate complex findings clearly, which is key for roles like Data Scientist.
✨Ace the Interview
Prepare for interviews by practising common data science questions and case studies. Be ready to discuss your past projects and how you've applied statistical techniques or machine learning. Remember, it's all about showing how you can translate data into actionable insights!
✨Apply Through Our Website
Don't forget to check out our website for job openings! Applying directly through us can give you an edge, as we love seeing candidates who are proactive and engaged with our platform. Plus, it’s a great way to get noticed by our hiring team!
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience as a data scientist, especially in data-intensive environments. We want to see your advanced Python skills and any relevant projects that showcase your ability to analyse complex datasets.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain how your analytical skills can support our commercial strategy and decision-making. Don’t forget to mention your interest in energy markets or related fields if applicable.
Showcase Your Communication Skills: We need someone who can translate complex data into clear insights for non-technical stakeholders. Highlight any experiences where you’ve successfully communicated quantitative findings to diverse audiences.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Mint Selection | B Corp
✨Know Your Data Inside Out
Before the interview, dive deep into the types of data you’ll be working with. Familiarise yourself with market data, asset performance metrics, and any relevant statistical models. Being able to discuss specific examples of how you've used data to drive decisions will impress your interviewers.
✨Showcase Your Python Skills
Since advanced Python skills are crucial for this role, prepare to demonstrate your proficiency. Bring along examples of your work, such as scripts or projects that highlight your data manipulation, feature engineering, and machine learning capabilities. Be ready to explain your thought process and the impact of your analyses.
✨Communicate Clearly and Confidently
You’ll need to translate complex data insights into clear narratives for non-technical stakeholders. Practice explaining your past projects in simple terms, focusing on the 'why' and 'how' rather than just the technical details. This will show your ability to bridge the gap between analytics and commercial decision-making.
✨Understand the Industry Context
Brush up on your knowledge of energy markets, commodities, and trading-driven performance metrics. Being able to discuss current trends or challenges in these areas will demonstrate your genuine interest and understanding of the industry, making you a more compelling candidate.