- Company Name
- Streem Energy
- Job Title
- Data Scientist – Renewable Energy & Forecasting
- Job Description
-
**Job title:** Data Scientist – Renewable Energy & Forecasting
**Role Summary:**
Responsible for developing, deploying, and maintaining predictive models for wind and solar production, revenue anomaly detection, and pricing within a renewable energy SaaS platform. Owns end‑to‑end data pipelines, model lifecycle, and client-facing explanations, working closely with the CTO and product stakeholders in a fast‑paced startup environment.
**Expectations:**
- 0–5 years data science experience, preferably in energy or utilities.
- Graduate of a top‑tier engineering, computer science, or applied mathematics program (Bachelor or Master).
- Strong capacity for independent ownership, rapid iteration, and clear communication with non‑technical audiences.
**Key Responsibilities:**
- Build and maintain scalable data ingestion and preprocessing pipelines.
- Design, train, and evaluate time‑series and machine‑learning models for production/solar forecasting, anomaly detection, and pricing.
- Deploy models into production (containers, orchestration, monitoring).
- Set up automated monitoring of data quality and model performance; trigger retraining pipelines as needed.
- Collaborate with product, business, and client teams to translate requirements into data‑driven solutions.
- Explain model behavior, results, and uncertainties to clients and internal stakeholders.
**Required Skills:**
- Expertise in machine learning, statistics, and time‑series analysis (ARIMA, Prophet, RNN, XGBoost, etc.).
- Solid data engineering: ETL, data quality, iteration, and monitoring; proficiency in Python (pandas, numpy, scikit‑learn, torch/tensorflow).
- Experience with model deployment and ops (Docker, Kubernetes, Airflow, MLflow).
- Strong analytical mindset, attention to detail, and a proactive startup mentality.
- Excellent written and verbal communication; ability to explain complex insights to non‑technical audiences.
**Required Education & Certifications:**
- BA/BS in Engineering, Computer Science, Applied Mathematics, or related field; or an MS/PhD in Machine Learning, Data Science, or Applied Mathematics.
- Recognition of coursework or certifications in data science, machine learning, or deep learning is an advantage but not mandatory.
**Nice to Have:**
- Knowledge of meteorological models, weather data ingestion, and wind/solar forecasting.
- Familiarity with generative models, advanced ML architectures, pricing models, and revenue forecasting.
- Prior experience in SaaS or deep‑tech startup environments.