Freelance ML / Signal Processing Engineer Time-Series Movement Data

Looking to leverage portable sensor data to analyze human movement and generate structured performance insights. I’m looking for a freelance ML / signal processing engineer to help improve a Python-based data pipeline that processes time-series sensor data and converts it into reliable movement summaries. The goal is to improve robustness, evaluation, and practical downstream outputs that can feed a user-facing dashboard or report. What you’ll work on: Clean and process time-series sensor data from IMU-style sources Improve event detection, segmentation, and classification logic Build evaluation workflows against manually reviewed data Add confidence scoring and error diagnostics Help define clean structured outputs for downstream product/reporting use Document how to run, validate, and improve the pipeline Ideal background: Strong Python Time-series analysis Signal processing ML model evaluation Experience with accelerometer/gyroscope/IMU data is a plus Experience with sports, wearables, biomechanics, healthtech, or movement analysis is a plus Deliverables for initial sprint: Improved pipeline performance on existing sample data Clear evaluation metrics and error analysis Structured JSON-style output format for downstream use Short technical documentation and recommended next steps