Data analyst engineer

Company Description

Starbird AI leverages advanced AI, sensor fusion, and digital signal processing (DSP) technologies to transform the electromagnetic spectrum into a reliable, mission-critical sensor platform. Our innovative solutions ensure operational awareness and control in environments where traditional sensors fall short. We specialize in maintaining critical capabilities in contested and denied operational scenarios. At Starbird AI, we strive to push technological boundaries to create cutting-edge tools that empower our clients.

What You’ll Do

- Build and maintain data pipelines from our navigation / DSP systems.

- Clean, synchronize, and label data, with a strong focus on time and sensor alignment.

- Perform deep data analysis and visualization (BI Tolls).

- Prepare datasets for AI/ML models (feature engineering, dataset splitting, reproducible pipelines).

- Organize and process data in the cloud (e.g., AWS/Azure).

- Work closely with the algorithm lead on experiments, evaluation, and reporting.What You Bring:

- BSc or higher in Electrical Engineering or in Computer Science with a focus on data / signal processing / machine learning.

- Strong Python skills, including pandas, numpy, and plotting libraries.

- Practical experience working with real-world data, 2-3 years.

- Basic experience with at least one cloud provider (e.g AWS / Azure ).

- Comfortable with Git and Linux environments.

- Strong analytical mindset and ability to work independently.

- Openness to learn, grow, and adapt in a fast-changing startup environment (curious, proactive, and comfortable with change).

- Experience with time-series or signal data. -advantage

- Experience with ML libraries (scikit-learn, PyTorch, TensorFlow). - advantage

- Familiarity with DSP / RF / navigation domains. - advantage

Must - have

- BSc or higher in Electrical Engineering or in Computer Science with a focus on data / signal processing / machine learning.

- Strong Python skills, including pandas, numpy, and plotting libraries.

- Practical experience working with real-world data, 2-3 years.

- Basic experience with at least one cloud provider (e.g AWS / Azure ).

- Comfortable with Git and Linux environments.

- Strong analytical mindset and ability to work independently.

- Openness to learn, grow, and adapt in a fast-changing startup environment (curious, proactive, and comfortable with change).Nice-to-have:

- Experience with time-series or signal data.

- Experience with ML libraries (scikit-learn, PyTorch, TensorFlow).

- Familiarity with DSP / RF / navigation domains.