At a Glance
- Tasks: Create predictive models and interactive analytics for global commodity markets using data science and AI.
- Company: Join ICIS, a leading data services provider in the energy and petrochemical industries.
- Benefits: Enjoy competitive perks like fitness support, extra leave for social engagement, and professional development.
- Other info: Be part of a dynamic team with a supportive culture and excellent career growth opportunities.
- Why this job: Make a real impact by shaping next-gen AI products that influence global market decisions.
- Qualifications: Experience in Python, SQL, and data modelling; strong communication skills are a must.
The predicted salary is between 63000 - 77000 £ per year.
About ICIS
ICIS is part of Risk Solutions Group (RSG), a division of RELX Group, a FTSE 20 company with revenues of $12.6 billion in 2025 and an employee base of over 37,000 people, serving customers in 180+ countries. ICIS makes some of the world's most important markets more trusted and predictable by providing data services, thought leadership and decision tools. We exist to help businesses in the energy, petrochemical and fertilizer industries make strategic decisions, mitigate risk, improve productivity, and capitalise on new opportunities.
Job Purpose
Are you passionate about applying data science, AI and analytics to solve complex business problems and create products that customers love? At ICIS, we're building the next generation of data-driven and AI-powered solutions for global commodity markets. As a Senior Data Scientist, you will join 30+ experienced Data Scientists in our Analytics Hubs in Karlsruhe or London.
Responsibilities:
- Create and continuously improve analytical commodity market models in Python.
- Co-develop with our analysts & engineers strong quantitative market models, such as demand modelling, supply modelling for capacity & cost, storage, trade & transport modelling, market balance & market price forecasting.
- Connect, clean, and impute freight, pricing, and supply/demand datasets from diverse internal and external sources.
- Turn raw, imperfect and incomplete data into actionable market insight.
- Create interactive analytics, planning and decision support tools that utilize data & models (e.g., Dash by Plotly).
- Deliver data and models into ICIS Data Lakehouse and shared platforms.
- Translate gained domain knowledge back into models and build a deep understanding of operation and decision making in our markets.
- Work goal-driven and self-organized with own project management responsibility on developments from day 1.
- Guide and support others in the development of models as well as create hands-on own implementations of framework enhancements.
Requirements:
- Strong communication and engagement, ability to explain complex concepts simply to stakeholders.
- Production-ready code in Python and SQL, using AI-code generation and Spec-Driven-Development in a productive & manageable way, familiar with common Data Science & analytics libraries.
- Data modelling, transformation, and visualization (e.g., Python Dash).
- Experience with software development (modularisation, versioning e.g., with GIT, tests, understandable code), with containerization (Docker) and orchestration (Airflow).
- Habit of starting simple first to get buy-in early and iterate on feedback to add value.
- Curiosity & desire to understand the world.
- A plus: existing knowledge of the chemical industry, Databricks & Snowflake.
Why Join ICIS?
- Work on Problems That Matter: global organizations make better decisions using data, analytics and AI.
- Build the Future of AI in commodity markets: Play a key role in shaping next-generation AI products and capabilities that will influence the future of our business and our industry.
- Work with Exceptional People: Join a multidisciplinary team of data scientists, engineers, economists, industry experts and product leaders who are passionate about innovation and customer impact.
- Enjoy Corporate Benefits: e.g., support for fitness studio, pension & public transport, 20 days work from anywhere and 4 days extra leave for social & sustainability engagement and ongoing learning and professional development opportunities.
Join a Team That Loves What It Does
Our Data Science team combines the energy of a start-up with the support and stability of a global organization of more than 37,000 employees. In 2025, our Data Science team achieved an Employee Net Promoter Score (eNPS) of 81, reflecting a highly engaged and supportive culture. ICIS is committed to building an inclusive workplace where everyone can thrive.
If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.
We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
Type: Full time
Senior Data Scientist/Artificial Intelligence Engineer in London employer: LexisNexis Risk Solutions Group
LexisNexis Risk Solutions is an exceptional employer that fosters a culture of innovation and operational excellence, particularly in the dynamic field of data management. Employees benefit from comprehensive training and mentorship opportunities, ensuring continuous professional growth while working on cutting-edge technologies in a collaborative environment. Located in Alpharetta, GA, the company offers competitive compensation, including an annual incentive bonus, and a commitment to employee well-being through tailored benefits that enhance work-life balance.
Contact Details:
LexisNexis Risk Solutions Group Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist/Artificial Intelligence Engineer in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like LexisNexis Risk Solutions Group!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Data Scientist/Artificial Intelligence Engineer at LexisNexis Risk Solutions Group.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like LexisNexis Risk Solutions Group.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Data Scientist/Artificial Intelligence Engineer at LexisNexis Risk Solutions Group, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Senior Data Scientist/Artificial Intelligence Engineer in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at LexisNexis Risk Solutions Group, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at LexisNexis Risk Solutions Group. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at LexisNexis Risk Solutions Group
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at LexisNexis Risk Solutions Group!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
