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.
Your mission is to:
- + 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.
You could be a match if you are or have:
- + At least 2 years of experience in the 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.
- Comfortable working with Git, code reviews, and Agile methodologies.
- Strong command of written and spoken English.
- Desirable
- Experience with AWS (or another cloud provider), using Terraform
- Experience with containerization (Docker) and orchestration (Kubernetes)
We are a dynamic company dedicated to nurturing connections and innovating solutions to tackle market challenges head-on. If you thrive on customer satisfaction and turning ideas into reality, then you’ve found your ideal destination. Are you ready to embark on this exciting journey with us?
We make things happen
We act decisively and with purpose, going the extra mile.
We build together
We foster relationships and develop creative solutions to address market challenges.
We are here to help
We are accessible and supportive to colleagues and clients with a friendly approach.
Our People Pledge
Don’t meet every single requirement? Research shows that women and people of color are less likely than others to apply if they feel like they don’t match 100% of the job requirements. Don’t let the confidence gap stand in your way, we’d love to hear from you! We understand that experience comes in many different forms and are dedicated to adding new perspectives to the team.
Kpler is committed to providing a fair, inclusive and diverse work-environment. We believe that different perspectives lead to better ideas, and better ideas allow us to better understand the needs and interests of our diverse, global community. We welcome people of different backgrounds, experiences, abilities and perspectives and are an equal opportunity employer.
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.