Kpler3mo ago

Data Scientist

AthensFull-timemid

Data ScienceData ScientistDataData & AI

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Overview

At Kpler, we are dedicated to helping our clients navigate complex markets with ease. By simplifying global trade information and providing valuable insights,

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Data ScienceData ScientistDataData & AI

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 700 experts from 35+ 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.

Kpler are looking for a Data Scientist for our and Gas and Power teams, who are responsible for the enhancement of our cross commodity offering. With the energy transition, more and more of our users are interested in getting access to both Gas and Power data. This role is to improve our value by implementing models and algorithms, that will aggregate data from both teams to present a unified view on future forecasts, including but not limited to; storage, pipeline and consumption.

Maintain and enhance the existing consumption forecasts per country pipeline

Develop new sector level gas consumption forecasts and align with the current gas generation for power forecast

Apply machine learning or statistical techniques to solve complex problems.

Use current MLOps platform to run R&D and expand our forecasts to new geographies or domains

Discuss the roadmap in collaboration with the product team.

Collaborate with engineers to integrate model outputs into APIs and customer-facing applications.

Improve model robustness, performance, and interpretability.

Contribute across the full lifecycle, from initial data exploration and research to production deployment.

At least 2 years of experience in a DS role, deploying models into production

Experience developing and deploying models using MLOps platforms (Dataiku, Databricks, Sagemaker, etc.)

Familiar with some software engineering best practices.

Proven experience delivering end-to-end ML solutions that produce business value.