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# Analytics Engineer

- **Company:** WindESCo Inc.
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Data Visualization, Relational Databases, Supervisory Control and Data Acquisition (SCADA), Python (Programming Language), Signal Processing, SQL Databases, Data Lakes
- **Published:** September 4, 2026
- **Apply:** https://windesco.recruiterbox.com/

## About the Role

To support our growth, we are looking for a Wind Energy Analytics Engineer to apply our proprietary algorithms to identify performance improvement opportunities in wind turbines and wind farms. The position requires wind turbine knowledge, attention to detail, innovative thinking, and problem-solving ability. You will need to be well organized, be able to innovate under deadline, and be able to communicate and collaborate effectively with others., * You are passionate about renewable energy and translating insights into results.

 * You are an innovative thinker who loves applied problem-solving in a fast-paced environment.
 * Bachelor's degree in STEM with 2+ years of relevant experience or Master's degree in STEM and relevant experience.
 * Experience with Python programming for technical computing.
 * Basic understanding of newtonian physics, mechanics, electrical energy, aerodynamics, and control systems.
 * Strong technical communication and organization skills.
 * Eligible to work in the US., The ideal candidate will have one or more of the following:
 * Experience analyzing wind turbine SCADA data
 * Understanding of wind turbine structural design, aerodynamics, controls or power electronics
 * Knowledge of signal analysis and control systems design
 * Familiarity with relational databases (SQL) and data lakes
 * Experience with data visualization and graphics design for communication of technical information

## Description

* Analyze and model turbine behavior using SCADA data.
 * Find anomalies in data and wind turbine behavior, develop effective visualizations, and support the automation of this process with Python.
 * Translate findings in data into real-world issues or corrections
 * Work collaboratively with other analytics engineers for continuous team improvement
 * Effectively communicate anomalous findings to external audiences of all technical levels


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