About StormGeo

Informed by nature, powered by technology We are a leading technology provider enabling weather-sensitive companies to navigate operational challenges in dynamic environments and volatile markets. With nature and weather intelligence at our core, our technological innovations and human expertise transform data into actions that safeguard people, industries, and nature for a sustainable future. For us, it's about more than just business; it's a legacy we are proud to build.

StormGeo is a truly global company with innovative and passionate team members from all over the world, offering actionable insights that empower the decision-making of shipping, energy, and weather-sensitive companies worldwide 24/7/365.

Since 2021, StormGeo has been part of Alfa Laval. Our shared goal is to accelerate success for our customers, our people, and our planet. We strongly believe that curiosity is the spark behind great ideas – and great ideas drive progress.

About the role

As a Senior Data Scientist at StormGeo, you will play a key role in advancing the quality, accuracy, and reliability of our operational forecasts. You will develop, validate, and deploy data-driven models that enhance forecast performance and scalability, working in close collaboration with meteorologists, oceanographers, and software engineers.

In this role, you will combine your technical expertise in data science and machine learning with a deep understanding of environmental and geospatial data. This is an exciting opportunity for an experienced data scientist who thrives in a research-driven, applied environment, and who wants to see their work make a tangible impact in the energy, shipping, and weather intelligence industries.

The position is based in Bergen, or Oslo, Norway.

Main responsibilities

• Develop, calibrate, and operationalize ML/AI models that enhance the accuracy and consistency of weather and ocean forecasts.
• Design and maintain transparent evaluation frameworks for both offline and live systems, using metrics such as error reduction, reliability, and forecast skill improvement; perform structured comparison tests between model versions.
• Analyze sources of error, bias, and drift, and establish systems for continuous monitoring, alerting, and automated model retraining.
• Collaborate closely with experts in meteorology, oceanography, and related sciences to translate physical understanding into model inputs and design constraints.
• Build robust data pipelines for ingestion, quality control, and feature preparation, while contributing to best practices for managing and deploying models in production environments.
• Optimize model performance and computational efficiency to meet the operational requirements of real-time forecasting.
• Document methodologies and findings thoroughly, and communicate insights, limitations, and trade-offs clearly to both technical and business audiences.
• Take ownership of models and systems and share expertise through code reviews and collaborative discussions.

Requirements

• Experience in applied ML or Data Science, with a focus on time series, forecasting, or spatiotemporal modeling.
• Proficiency in Python (pandas, NumPy, scikit-learn, PyTorch/JAX/TensorFlow, XGBoost/LightGBM) and SQL; solid understanding of software engineering practices (testing, type hints, code review).
• Experience with probabilistic forecasting and uncertainty of quantification (ensembles, calibration, quantile/regression methods, reliability analysis).
• Familiarity with numerical forecasting systems or other data-intensive prediction domains.
• Practical MLOps experience, including feature stores, model registries, orchestration, containerization, CI/CD, and cloud platforms (AWS, Azure, or GCP).
• Strong background in experimental design, model validation, and statistical inference, with experience handling sparse or noisy real-world data.
• Self-driven and accountable: able to take initiative, challenge assumptions, and lead end-to-end projects. Mentor peers and influence technical direction and roadmaps through expertise and critical thinking.
• Good collaboration and communication skills, with the ability to work effectively in an interdisciplinary team environment.
• Education: Master’s or Ph.D. in Computer Science, Data Science, Applied Mathematics, Physics, Engineering, or another quantitative field.

Company offers

• Global mission - Every day, we enable our clients to navigate a changing environment by unlocking the value of data.
• Smart, creative, and innovative environment, where you'll work alongside a talented and supportive team of professionals.
• Hybrid Work Model.
• International development opportunities to support your professional growth.

If you're a skilled Data Scientist with a passion for impactful decisions and working with a dynamic team, apply now to join StormGeo!

We value diverse perspectives and welcome candidates from all backgrounds and industries. StormGeo offers a stimulating international environment where we challenge, encourage, and support each other. Get a glimpse of our culture and what it’s like to be part of our team by watching this short video: StormGeo.

How to Apply: To apply for the position, kindly utilize the provided application link. It's important to note that applications and CVs submitted via email will not be considered. We will be reaching out to suitable candidates continuously, so we encourage you to submit your application promptly if you are keenly interested.