At a Glance
- Tasks: Analyse global oil markets using advanced coding and analytical skills.
- Company: Join BloombergNEF, a leader in energy market research.
- Benefits: Competitive salary, dynamic work environment, and opportunities for growth.
- Other info: Collaborative team culture with diverse perspectives and innovative thinking.
- Why this job: Make an impact in the energy sector while developing your analytical expertise.
- Qualifications: Experience in commodities, strong Python and SQL skills required.
The predicted salary is between 44550 - 54450 £ per year.
BloombergNEF is seeking an Oil Markets Analyst for an initial 12 month contract who combines sharp commodity market judgment with advanced analytical and coding skills to join our team in London. You will turn complex, imperfect datasets into clear, defensible views on global oil supply, demand, trade flows and prices. You will also own the data, models and methodologies that underpin those views. Using Python, SQL, Bloomberg Terminal data, proprietary BNEF datasets and external sources, you will identify shifts in market fundamentals early, test competing hypotheses and deliver insights that help clients anticipate what could move the market next.
About BloombergNEF: BloombergNEF (BNEF) is a strategic research provider covering global commodity markets and the transformative forces reshaping energy systems and infrastructure. Our experts assess the technological, economic and policy drivers that underpin the transition to a cleaner, more resilient energy economy. We help senior leaders in corporate strategy, finance, policy and commodity trading navigate change and generate opportunities.
Our Team: You will be based in our London office and work as part of the global oil markets research team, alongside colleagues in London, New York and Singapore. Our work involves tracking and forecasting global oil fundamentals and prices. We operate at the intersection of fundamental commodity analysis, data science and client decision-making. The oil markets team works closely with BNEF’s upstream oil, downstream oil and chemicals, renewable fuels and commodity product teams. This gives analysts exposure across the full oil value chain and helps them understand how developments in production, refining, logistics, consumption and financial markets interact. Our research is used by leading organizations across oil and gas, commodity trading, banking and finance, utilities, government and corporate strategy.
BNEF Team Ethos: To succeed at BNEF we need people who can work in an independent manner and show initiative to develop their own viewpoints, yet be collaborative with colleagues. We don’t rely on the status quo, we look for innovative yet pragmatic thinking that turns big ideas into real insights and impact. Working at BNEF sometimes feels chaotic; we need teams that are both dynamic and structured to generate the unique perspectives our clients really value. Our teams are diverse, creative, focused, and fun!
The Role: This is a combined commodity research and analytical product role. You will spend a substantial portion of your time using Python, SQL, Microsoft Excel and other analytical tools to build and maintain datasets, automate recurring analysis, develop market models and create indicators that improve our understanding of global oil fundamentals and pricing behavior. Coding is a core part of the day-to-day role, not a supporting activity. Analysts are expected to build and maintain reliable analytical workflows as part of producing their market research. You will use these tools to develop independent views on short- and medium-term oil market developments, publish regular research and contribute to forecasts and scenarios that matter to market-facing clients. You will work closely with BNEF’s data, engineering and product teams to turn successful analytical prototypes into reliable, scalable tools and client products. You will also collaborate with commercial and client-facing teams to ensure our research addresses important client questions and creates business impact for Bloomberg and BNEF.
You will need to:
- Own and improve models covering oil market fundamentals and prices
- Build automated, reproducible data pipelines to analyze large, complex datasets
- Design validation checks, tests and monitoring processes that maintain the accuracy and reliability of critical datasets and models
- Write clear, tested, documented and version-controlled code that colleagues can reuse
- Develop forecasts and scenarios and clearly communicate their assumptions, uncertainty and principal risks
- Monitor physical and financial market signals and connect them to changes in underlying fundamentals
- Identify new datasets and analytical methodologies that could provide BNEF clients with differentiated insight
- Work with data, engineering and product colleagues to turn research prototypes into reliable analytical products
- Publish clear, concise and decision-useful research for market-facing clients
You'll need to have:
- Relevant professional experience in commodities, energy markets, trading analytics, market intelligence or another data-intensive environment
- Demonstrated proficiency in Python for data manipulation, analysis and modeling, including experience working with large or complex datasets
- Practical experience using SQL and artificial intelligence (AI) to support research and improve efficiency
- Experience building analytical workflows that are reproducible, documented and maintainable, including familiarity with version-control systems such as Git
- Strong quantitative reasoning and the ability to select appropriate analytical methods without overcomplicating the analysis
- Strong Excel skills and the ability to work effectively across code-based and spreadsheet-based analytical workflows
- The ability to produce clear, decision-useful charts, visualizations and dashboards rather than simply present large volumes of data
- Excellent written and verbal communication skills in English, including the ability to produce concise research and explain complex market and technical questions to clients
- Strong attention to detail and a willingness to work directly with raw, incomplete or inconsistent data
- A bachelor’s degree in economics, finance, engineering, mathematics, statistics, computer science, data science, physics or another relevant quantitative discipline
- A commitment to inclusion and a demonstrated ability to collaborate effectively with colleagues from a variety of backgrounds
We'd love to see:
- Experience with time-series analysis, forecasting, econometrics, scenario modeling or uncertainty analysis
- Direct professional experience in oil, refined products, shipping, commodity trading, market intelligence or energy investment research
- Experience using application programming interfaces (APIs), cloud-based data tools, geospatial data, vessel-tracking data or other alternative datasets
- Familiarity with Python libraries used for data analysis and statistical modeling, such as pandas, Polars, NumPy, stats models and scikit-learn
If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.
BloombergNEF Oil Markets Analyst (12 months contract) in London employer: Bloomberg
Bloomberg is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. With a strong emphasis on employee growth, you will have access to numerous professional development opportunities while working in a cutting-edge environment that values your contributions to the data manufacturing infrastructure. Located in a vibrant city, Bloomberg provides unique advantages such as a diverse workforce and a commitment to work-life balance, making it a rewarding place to advance your career.
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We think this is how you could land BloombergNEF Oil Markets Analyst (12 months contract) in London
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We think you need these skills to ace BloombergNEF Oil Markets Analyst (12 months contract) in London
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at Bloomberg, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to Bloomberg, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab Bloomberg’s attention and show the tangible impact of your work.
How to prepare for a job interview at Bloomberg
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at Bloomberg.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at Bloomberg.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at Bloomberg.
