Overview
At Kpler, we are dedicated to helping our clients navigate complex markets with ease. By simplifying global trade information and providing valuable insights, we empower organisati
Full job description
At Kpler, we are dedicated to helping our clients navigate complex markets with ease. By simplifying global trade information and providing valuable insights, we empower organisations to make informed decisions in commodities, energy, and maritime sectors.
Since our founding in 2014, we have focused on delivering top-tier intelligence through user-friendly platforms. Our team of over 850 experts from 69 countries works tirelessly to transform intricate data into actionable strategies, ensuring our clients stay ahead in a dynamic market landscape. Join us to leverage cutting-edge innovation for impactful results and experience unparalleled support on your journey to success.
As a Machine Learning Engineer in the Power team, you will be instrumental to the development of the Power offering. You will be fully dedicated to a new product covering the Japanese power market. This product will adapt and expand as required, existing modelling infrastructure to the Japanese power market in order to build fundamental forecasts.
Develop a deep understanding of existing models and adapt them to the Japanese Power market Develop new models, managing the entire lifecycle (Training, Evaluation, Backtesting, Tuning, Model selection etc). Integrate market signals from other commodities (LNG, coal) to enhance the quality of our forecasts Enrich the product and participate in the development of new features Build and improve monitoring and alerting tools and dashboards Discuss the roadmap in collaboration with the product team. Help the team build ambitious yet sustainable plans
Essential: BSc/MSc in computer science, computer engineering or equivalent Circa 3-5 years' of experience as a data focused Software Engineer (minimum 2 Years experience with Machine Learning) Significant experience working with Python Experience with Postgresql or similar data stores Machine learning R&D experience (Training, Evaluation, Backtesting, Tuning, Model selection) Data Science R&D experience (Statistics, Hypothesis testing) ML Engineering experience (model versioning, feature versioning) Comfortable working with Git, code reviews, and Agile methodologies Experience with time-series, events data, normalization, database design Understanding of performance optimization and caching strategies Great communication, ability to work asynchronously with team members in other countries Strong command of written and spoken English Desirable: Previous experience of the electricity/power markets Have experience with AWS (or another cloud provider), using Terraform Experience with Deep learning techniques Experience with orchestration tool Airflow on a production environment Experience with containerization (Docker) and orchestration (Kubernetes) Experience with a ML registry framework (e.g. MLFlow…) Knowledge on hexagonal architecture and medallion architecture Used monitoring solutions (Datadog, Grafana, etc...) Experience with NoSQL database Japanese speaker
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