Software Engineer in Data Science

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. This role will have an initial focus on supporting our GenAI tools, including our firmwide virtual assistant. Concretely this means you will:

• Implement: take the requirements from our broad range of commercial stakeholders and translate these into application features.
• Design: ensure we design and build the models and tools to meet the functional/non-functional requirements, as well as being supportable. The role will also help partner teams understand how they can support and integrate to the AI tools.
• Translate: act as a local champion for data science and AI, helping users adopt tools and articulate their changes and requirements to the wider team.

The individual will work both 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.).

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 can and wants to continue learning.

As a small team, everyone is expected to organize, prioritize and execute their own tasks; with a strong focus on maximizing 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’.

• Act as the primary point of contact in Houston for our GenAI toolset
• In conjunction with the global Data Scientists deliver models and solutions to business users, and other technology teams across a wide range of projects and technologies
• Develop, test, maintain software tools and data pipelines for machine learning
• Provide software engineering and design expertise and best practices (Python) with a focus on maintainability, performance, and reliability
• As needed, take ownership of key technical infrastructure
• Engage with projects at any point in their lifecycle, understand and debug bespoke applications; driving performance and reliability
• Manage relationships and priorities across projects, focused on maximising value
• Actively participating in and leading code reviews, experiment design and tooling decisions to help drive the team’s velocity and quality

• 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
• Master’s degree in Computer Science or a related field
• Ability and desire to learn and apply new technologies
• Ability to logically evolve an architecture from prototype to product, considering technical debt and delivery risk
• Collaborative approach to problem solving – ability to effectively pair program
• Effective technical communicator – both written and verbal; able to translate loose designs into documentation / process / operating model
• Experience with data engineering, APIs, and cloud platforms (ideally AWS) and containerization technologies (Docker)
• Experience with enterprise software development lifecycle and tooling including continuous integration and delivery concepts/technologies

• Experience with machine learning workflows, cloud‑scale machine learning infrastructure (including…