Data Scientist (Energy)

TL;DR

Data Scientist (ML/Forecasting): Implementing models and algorithms to aggregate Gas and Power data for unified forecasts of storage, pipeline, and consumption with an accent on cross-commodity intelligence. Focus on deploying end-to-end ML solutions via MLOps platforms and improving model robustness and performance.

Location: Hybrid (Hungary)

Company

hirify.global provides global trade information and insights for commodities, energy, and maritime sectors to empower informed decision-making.

What you will do

• Maintain and enhance consumption forecast pipelines per country.
• Develop sector-level gas consumption forecasts aligned with power forecasts.
• Apply machine learning and statistical techniques to solve complex business problems.
• Use MLOps platforms to run R&D and expand forecasts to new geographies or domains.
• Collaborate with product teams on roadmaps and engineers to integrate model outputs into APIs and applications.
• Oversee the full lifecycle from initial data exploration and research to production deployment.

Requirements

• At least 2 years of experience in a DS role with a track record of deploying models into production.
• Experience developing and deploying models using MLOps platforms (Dataiku, Databricks, Sagemaker, etc.).
• Proficiency in software engineering best practices, Git, and Agile methodologies.
• Strong command of written and spoken English.
• Proven ability to deliver end-to-end ML solutions that provide business value.

Nice to have

• Experience with AWS (or another cloud provider) and Terraform.
• Experience with containerization (Docker) and orchestration (Kubernetes).

Culture & Benefits

• Inclusive and diverse work environment committed to equal opportunity.
• Collaborative culture focused on innovation and solving market challenges.
• Supportive environment with a "People Pledge" to encourage applicants from diverse backgrounds.