Applied Machine Learning Researcher

About ESG Book

Arabesque S-Ray GmbH, now also trading as “ESG Book”, is a global leader in sustainability data and technology. Incubated by Arabesque in 2018, ESG Book combines cutting-edge technology and proprietary research. ESG Book’s wide range of cloud-based sustainability products and solutions are used by many of the world’s leading financial organisations which collectively manage over $120 trillion.

The company has offices in London, Frankfurt, Boston, Singapore, Delhi and Tokyo and serves clients worldwide from offices in Asia, Europe and North America. www.esgbook.com

Global Research Office

We are responsible for designing, building, and managing the sustainability data and research models. We are looking for technically competent, sustainability experts who like to work in a collaborative environment to innovate, advance, and contribute to the development of the company – and have impact on the research and products we create for investors and corporates. You will be part of the 85+ global data, research, and product office, and work on a wide variety of projects with a focus on building out climate and NetZero solutions. You will be involved in the core research and development, and responsible for new climate scoring analytics, visualizations of climate products on platform, and ensuring new climate products and solutions are well-understood by our global clients.

What you'll do

• Research and train models for a range of complex Applied ML tasks with a strong focus on NLP
• Design and implement machine learning model pipelines to improve efficiency, speed, and effectiveness of our ML operations
• Be collectively responsible for designing, developing and maintaining technical infrastructure to train and serve our Applied ML models at scale on cloud platforms (e.g. GCP, AWS)
• Be familiar with CI/CD systems to ensure quick release of new models
• Become a valued member of an autonomous, multi-functional team and contribute to growing the skills and knowledge of your peers
• Facilitate the collaboration with other specialists, researchers, data scientists and product owners to ensure we deliver the maximum value to our customers
• Work closely with our developers and MLOps engineers to design distributed system architectures to solve large scale problems

Requirements

• Minimum 3-5 years industry experience working on ML with exposure to industry projects using NLP
• Experience with containerisation (Docker) and orchestration (Kubernetes) technologies
• Extensive knowledge of NLP and be up to date with the latest advancements
• Knowledge of ML frameworks such as PyTorch, Keras, Sklearn and Huggingface
• You are proficient in a programming language such as Python or Java/Scala
• You can easily work with a range of data stores within the relational SQL world (PostgreSQL, BigQuery), NoSQL databases (Elasticsearch) and key-store databases
• You have a strong computer science and programming fundamentals
• You have a deep understanding of system design and data structures
• You care about quality; details and you know what it means to ship high-quality code that is easy to maintain and extend
• You are passionate about applying ML to Sustainability and ESG, as well as the impact of the products you create
• You can manage and lead groups of people across disciplines and are able to easily distil complex concepts to non-technical people
• Lead Applied ML research and manage a growing team

Benefits

• 30 Days Holiday (plus bank holidays)
• Enrolment into our options scheme
• Pension
• 10% time back for learning and development

Equal Opportunities

ESG Book is an equal opportunity employer, and all qualified applicants will be afforded equal employment opportunities without discrimination because of actual or perceived race, color, national origin, sex, age, religion, creed, disability, marital status, citizenship, ancestry, personal appearance, sexual orientation, gender identity or expression, political affiliation, military status, status as a protected veteran, genetic information or any other legally protected status.