Python / ML Consultant for UAV Sensor-Data Pipeline Review and Technical Mentoring

I am a master's researcher working on decentralized, edge-based fault detection for UAV swarms. I am seeking technical consultation, code review, and mentoring for my existing Python / Google Colab notebooks. The current scope focuses on sensor-data preprocessing, feature extraction, fault-classification pipelines, and reproducibility across TII, PADRE, and RflyMAD datasets. Required experience: - Python, pandas, NumPy, and scikit-learn - Sensor or time-series data preprocessing - Fault / anomaly detection - Review of data splitting, leakage risks, and model evaluation - Reproducible Jupyter / Google Colab workflows Initial task: Review one existing notebook and provide a concise technical report identifying confirmed issues, methodological concerns, and optional improvements. Please reference specific cells or functions and explain the reason for each proposed change. Do not rewrite the pipeline, change methodological decisions, or rerun experiments without my approval. Please include: 1. One or two relevant project examples and your personal role. 2. Your experience with sensor-data ML pipelines. 3. Your proposed scope, estimated hours, and fee for the review. 4. Whether you can explain findings in a live technical session. This engagement is for consultation and learning support, not thesis ghostwriting or completing assessed work on my behalf. Any assistance must comply with my university's rules. I need an initial technical review of one existing Google Colab notebook within 7 days of the contract start. The scope includes reviewing data preprocessing and ML evaluation, identifying issues, and providing a concise report explaining the recommended corrections. Any code modifications require my approval.