Our client is a prominent player in the energy and commodities trading sector, spanning various domains from oil to renewables and is committed to driving the energy transition. With a significant investment in renewable projects, they leverage their global presence to create value throughout the energy supply chain while focusing on low-carbon opportunities.

Responsibilities:

• 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 commercial side of the business, continuously looking for new ways how AI/DS can create value for the firm.
• 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 (including GenAI) 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

Qualification:

• 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

Requirements:

• Experience in the energy or commodities trading industry is desired but not mandatory, 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

What they 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 the company's operations

They will offer Work Visa sponsorship for the right candidate

Apply Now:

Contact Baran, Principal EMEA at Hiperpool, to apply and to find out more.

The compensation for this role is competitive depending on the preferred location and expereince.

The compensation range and benefits for this position are based on a full-time schedule for a full calendar year. The salary will vary depending on your job-related skills, experience, and location.

We encourage applications regardless of ethnic origin, race, religious beliefs, age, disability, gender or sexual orientation, and any other protected status as required by applicable law. If you require any adjustments or additional support during the recruitment process for any reason whatsoever, please let us know.

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