Company Description

Vitol is a leader in the energy sector with a presence across the spectrum: from oil through to power, renewables and carbon. From 40 offices worldwide, we seek to add value across the energy supply chain, including deploying our scale and market understanding to help facilitate the energy transition. To date, we have committed over $2 billion of capital to renewable projects, and are identifying and developing low-carbon opportunities around the world.

Our people are our business. Talent is precious to us and we create an environment in which individuals can reach their full potential, unhindered by hierarchy. Our team comprises more than 65 nationalities and we are committed to developing and sustaining a diverse work force. Learn more about us here.

Job Description

As our portfolio of work continues to grow, we are looking for a Desk Data Scientist to join our data science and machine learning team as well as the Crude trading desk. The individual will work closely with the data and machine learning specialists, software engineers and commercial teams to deliver machine learning models and applications. 

Being closely embedded in the trading business, the individual will need to be comfortable working with a variety of stakeholders and technologies.

The Desk Data Scientist at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing, exploratory analysis, model selection and tuning, and implementation of production models. The data we work with is often complex and messy, and a successful Data Scientist is always willing to delve into the data in order to achieve results.

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:

Being an energetic and enthusiastic member of a team uniquely positioned to bring the power of data to bear on the inner workings of the energy industry Ability to relate effortlessly with the Crude trading business, continuously looking for new ways how AI/DS can create value for the desk Exploring new datasets, extracting insights, and visualizing the results Leading design, development, and deployment of machine learning systems, bringing their technical knowledge and experience into the team, and using this to create real solutions to real problems Collaborating with cross-functional technology teams to gather requirements and ensure the solutions align with business objectives Helping integrate the team’s solutions into existing systems and platforms to provide seamless user experiences and scale adoption. Actively participating in code reviews, experiment design and tooling decisions to help drive the team’s velocity and quality Helping build data and machine learning expertise within the business through knowledge sharing

Qualifications

Essential Qualifications

Master's degree in Computer Science, Data Science, Machine Learning, or a related field. Ph.D. is a plus Fluency in Python with the ability to write clean, modular, well-documented code as well as a solid understanding of coding best practices 3-5+ years in industry developing and deploying machine learning models Extensive experience exploring and extracting insights from heterogeneous multi-dimensional data sets, and presenting complex data visually Time series modelling (both machine-learning and econometric approaches) Familiarity with cloud platforms (AWS) and containerization technologies (Docker) Excellent problem-solving skills, ability to work independently and in a team Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders Understanding of ML fundamentals and experience with ML frameworks Advanced coursework in math, statistics, and machine learning preferred Demonstrable attention to detail

Desired Experience

Experience in the energy or commodities trading industry, with knowledge of financial markets and trading concepts Experience integrating machine learning systems into interactive dashboards (e.g. Dash, Streamlit) and present use cases of machine learning to non-technical colleagues Application of a wide range of ML methodologies to real life applications Enterprise software development (systems design, code review, version control, etc.) Data orchestrators (Airflow, Dagster) and cloud-based ETL/ELT pipelines Awareness of continuous integration and delivery concepts/technologies 

Additional Information

Personal Characteristics

A self-motivated individual who thrives on seeing the results of their work make an impact in the business Strong communication skills, both verbally and in writing Proven ability to be flexible, work hard, and a sense for the art of the possible Methodical, organized and with an attention to detail - in general, in experimental design, and in code! Willingness to share their knowledge and learn from others An interest in learning about the commodities space Resourceful, able to think creatively and adapt in a dynamic environment Team player, with an open non-political style and a high level of integrity 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

What we offer

Competitive salary and benefits package Large diversity of projects with real-world impacts on a truly global scale Entrepreneurial environment within a flat hierarchy, where great ideas come to life quickly Close collaboration with various business units across our key regions (eg. London, Singapore, Houston, Geneva) A highly motivated DS and ML team comprised of experienced individuals with a supportive attitude and great team spirit Being part of the energy transition through increased emphasis on renewable & alternative energy sources at a pivotal moment in the industry Strong management commitment to incorporating machine learning into the future of Vitol’s operations