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Darwin Recruitment

Data Scientist

Darwin Recruitment, Berlin, New Hampshire, us, 03570


Data Scientist

Our client, a leader in autonomous systems, is seeking a

Data Scientist with a specialization in Signal Processing

to join their innovative team. This is a unique opportunity to work on high-impact projects at the intersection of AI, data science, and state-of-the-art technology, transforming sensor data into actionable insights for complex, real-world applications.

What You Will Be DoingIn this role, you will:

Develop sophisticated algorithms to analyze radar and sensor data, enabling detection, segmentation, and tracking.

Conduct detailed data analysis to reveal meaningful insights and patterns.

Build and optimize machine learning models to maximize performance and accuracy.

Prepare data through filtering, denoising, and normalization, making it suitable for advanced modeling and analysis.

Collaborate closely with cross-functional teams, including engineers, developers, and product managers, to translate project requirements into scalable, efficient solutions.

Deploy models to production, ensuring their robustness and scalability.

Document your work to support reproducibility and ongoing improvements.

Profile & RequirementsEducation:

Bachelor’s degree (minimum) in Computer Science, Electrical Engineering, Data Science, or a related field; an advanced degree (Master’s or Ph.D.) is a plus.

Experience:

3+ years in a commercial data science role, particularly in signal processing for sensor data, radar, SAR, or maritime radar systems.

Technical Skills:

Proficiency in

Python

and familiarity with

MATLAB

and

C++ .

Strong knowledge of signal processing techniques and machine learning frameworks like

TensorFlow, PyTorch, TensorRT , or

scikit-learn .

Experience with Jupyter Notebooks for experimentation and model development.

Knowledge of radar systems and signal processing specific to radar and SAR data.

Familiarity with cloud platforms (GCP preferred, AWS or Azure acceptable) and experience with taking ML models into production.

Understanding of DevOps practices, including GIT, CI/CD, and telemetry tools.

Soft Skills:

Strong analytical and problem-solving abilities.

Excellent verbal and written communication skills.

Team-oriented with a proactive, adaptable approach to dynamic environments.

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