Senior Data Scientist: Wind Forecasting & Renewables

Headway Tek Inc; Juno Beach (FL); On-site; USD 140,000 - 190,000; Full time

Job summary

Headway Tek Inc. seeks a Senior Data Scientist to lead wind, solar, and load forecasting initiatives for NextEra Energy operations.

The role emphasizes productionizing forecasting models, evaluating weather‑provider inputs, and collaborating with data engineers and operations to ensure reliable forecasts. The ideal candidate will combine strong statistics, machine learning, meteorology, and energy domain knowledge to deliver robust, scalable forecasting solutions with production readiness and

Qualifications

• Advanced proficiency in Python and data‑science libraries (pandas, NumPy, scikit‑learn).
• Experience developing and deploying forecasting/time‑series models.
• Strong knowledge of feature engineering, regression, time‑series methods, and ensembles.
• Experience integrating weather APIs, NWP forecasts, SCADA, and external data feeds.
• Ability to evaluate weather‑provider performance and impact on forecast accuracy.
• Strong SQL, data analysis, and software development practices.

Responsibilities

• Develop and productionize Wind, Solar, and Load forecasting models.
• Perform feature engineering and model validation/backtesting.
• Evaluate weather and NWP providers for accuracy, latency, and coverage.
• Monitor forecast performance and diagnose forecast misses and data issues.
• Collaborate with data engineers, DevOps, and stakeholders to deploy forecasting solutions.
• Build dashboards and tools to communicate forecast performance and operational impact.

Skills

Python

Pandas

NumPy

scikit-learn

statsmodels

LightGBM

XGBoost

Forecasting models

Time-series

SQL

AWS

Git

Communication

Tools

AWS SageMaker

EC2

S3

Lambda

ECS

Step Functions

CloudWatch

Job description

Headway Tek Inc. seeks a Senior Data Scientist to lead wind, solar, and load forecasting initiatives for NextEra Energy operations.

The role emphasizes productionizing forecasting models, evaluating weather‑provider inputs, and collaborating with data engineers and operations to ensure reliable forecasts. The ideal candidate will combine strong statistics, machine learning, meteorology, and energy domain knowledge to deliver robust, scalable forecasting solutions with production readiness and