Data Scientist - Monitoring

Renewcast builds high-accuracy wind & solar forecasting using advanced ML and weather modeling. The problem is scientifically rich, full of messy real-world constraints, and offers immediate impact. We work transparently, move quickly, and value people who thrive in applied environments where iteration matters more than perfection.

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Your Role

You will join the modeling team as a mid-level data scientist who boosts our capability across both experimentation and production.

Improve forecasting models through well-structured experiments and feature development.

Work with weather, NWP, and geospatial data — learning the domain deeply over time.

Strengthen the team’s ability to respond to production challenges, from monitoring signals to diagnosing unexpected model behavior.

Help keep deployments reliable by contributing to batch inference workflows, retraining, and drift checks.

Participate in roadmap conversations without being expected to drive architectural decisions.

Bring enthusiasm for the mission and a willingness to operate in an evolving, imperfect, high-impact environment.

This role is a fit for someone who loves real-world ML, enjoys “getting their hands dirty,” and wants to grow alongside other experienced data scientists.

What You Will Do

Contribute to forecasting model development (experimentation, features, evaluation).

Clean, analyze, and transform meteorological and time-series datasets.

Run experiments that steadily improve performance and robustness.

Support model deployments: scheduled inference, retraining workflows, monitoring.

Investigate data/model issues in production and help drive resolutions.

Ensure clarity and reproducibility through documentation and structured workflows.

Collaborate with the lead scientist on priorities and modeling directions.

Must-Have Skills

Solid Python skills and experience with PyTorch or comparable DL frameworks.

Intuition for time-series modeling or spatiotemporal data.

Experience deploying models (batch jobs, APIs, pipelines) and debugging production behaviours.

Ability to work effectively in a dynamic environment with evolving tooling and datasets.

Clear communication skills, eagerness to learn, and enthusiasm for renewable-energy challenges.

Bonus Points

Exposure to weather/NWP or other scientific datasets.

Experience with large-array formats (Zarr, Icechunk) or distributed frameworks.

Familiarity with model monitoring, retraining cadence, or drift detection.

Interest in probabilistic or ensemble forecasting.

Why Join Renewcast

Work on one of the most challenging and meaningful forecasting problems.

Directly contribute to increasing the adoption of clean energy and accelerating the transition to a net-zero future.

Combine scientific curiosity with real-world model deployment.

Collaborate with experienced DS, MLOps, and engineering teammates.

High autonomy, clear ownership, and direct impact on the product and mission.

EU-friendly environment with an emphasis on growth and learning.

What We Offer

Competitive compensation.

Hybrid flexibility; offices in Tallinn and Rome. xrdbqlu

High-ownership work environment with visibility to leadership.

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