Desk Data Scientist

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

Requirements

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