Company Description
Vitol is a leader in energy and commodities. Vitol produces, manages and delivers energy and commodities to consumers and industry worldwide. In addition to its primary business of trading, Vitol is invested in infrastructure globally, with $10+billion invested in long-term assets.
Vitol’s customers include national oil companies, multinationals, leading industrial companies and utilities. Founded in Rotterdam in 1966, today Vitol serves its customers from some 40 offices worldwide. Revenues in 2023 were $400bn.
For more information: vitol.com
Job Description
As our portfolio of work continues to grow, we are looking for an experienced Software Engineer to join our global data science and machine learning team, to help us:
1. Lead: Make the right technology choices in the context of the team’s projects
2. Design: Ensure we design and build the models and tools to meet the functional/non-functional requirements, as well as being supportable
3. Explore: Help the team understand and exploit emerging technologies
4. Improve: Improve our software engineering skillsets, and grow as a team
The individual will work predominantly with our data scientists and machine learning engineers, but will also need to directly engage with the commercial teams (across trading, operations, support functions, etc.) as necessary.
The role will also act as a bridge between the Data Science team and other technology teams for areas like application integration, data sourcing, infrastructure and tooling.
For the successful candidate, this role will give them exposure across the machine learning lifecycle, being able to apply their skills wherever they can add value, from working with business stakeholders to help define the project, to data collation through to solution design and model implementation.
We are looking for a candidate who brings both a breadth and depth of experience, from a theoretical and practical perspective; but equally someone who is able to and wants to continue learning.
As a small team, everyone is expected to organise, prioritise and execute their own tasks; with a strong focus on maximising the business value from their actions. This means the individual will need to be comfortable working on multiple projects simultaneously, managing competing priorities and stakeholder requirements.
The successful candidate will join a team of experienced, collaborative practitioners, who are (pragmatically) solving some of the most challenging and impactful problems the energy industry is facing; as well as pushing the boundaries around the ‘art of the possible’.
Core Responsibilities include:
5. In conjunction with the Data Scientists deliver models and solutions to business users, and other technology teams across a wide range of projects and technologies
6. Develop, test, maintain software tools and data pipelines for machine learning
7. Provide software engineering and design expertise and best practices (Python) with a focus on maintainability, performance, and reliability
8. Take ownership of key technical infrastructure
9. Engage with projects at any point in their lifecycle, understand and debug bespoke applications; driving performance and reliability
10. Manage relationships and priorities across projects, focused on maximising value
11. Actively participating in and leading code reviews, experiment design and tooling decisions to help drive the team’s velocity and quality
Qualifications
Essential Qualifications
12. 3-5+ years in industry; fluency in Python with ability to design and write clean, modular, well-documented code and a solid understanding of coding best practices
13. Master's degree in Computer Science or a related field
14. Ability and desire to learn and apply new technologies
15. Ability to logically evolve an architecture from prototype to product, considering technical debt and delivery risk
16. Collaborative approach to problem solving - ability to effectively pair program
17. Effective technical communicator - both written and verbal; able to translate loose designs into documentation / process / operating model
18. Experience with data engineering, APIs, and cloud platforms (AWS/Azure/GCP) and containerization technologies (Docker)
19. Experience with enterprise software development lifecycle and tooling including continuous integration and delivery concepts/technologies
Desired Experience
20. Experience with machine learning workflows, cloud scale machine learning infrastructure (including LLMs), big data technologies (e.g. Spark)
21. Experience in the energy or commodities trading industry, with knowledge of financial markets and trading concepts
22. Data orchestrators (Airflow, Dagster) and cloud-based ETL/ELT pipelines
Personal Characteristics
23. A self-motivated individual who thrives on seeing the results of their work make an impact in the business
24. Strong communication skills, both verbally and in writing
25. Proven ability to be flexible, work hard, and a sense for the art of the possible
26. Methodical, organized and with an attention to detail - in general, in experimental design, and in code!
27. Willingness to share their knowledge and learn from others
28. An interest in learning about the commodities space
29. Resourceful, able to think creatively and adapt in a dynamic environment
30. Team player, with an open non-political style and a high level of integrity
31. Desire to be a thought-partner in a fast-growing team, and make an impact at a business that sits at the heart of the world’s energy flows
Additional Information
What we offer
32. Competitive salary and benefits package
33. Large diversity of projects with real-world impacts on a truly global scale
34. Entrepreneurial environment within a flat hierarchy, where great ideas come to life quickly
35. Close collaboration with various business units across our key regions (eg. London, Singapore, Houston, Geneva)
36. A highly motivated DS and ML team comprised of experienced individuals with a supportive attitude and great team spirit
37. Being part of the energy transition through increased emphasis on renewable & alternative energy sources at a pivotal moment in the industry
38. Strong management commitment to incorporating machine learning into the future of Vitol’s operations