Senior Data Scientist - Time Series Analysis

Description :

- Design and implement pre-processing pipelines for signal and time series data.

- Build algorithms/models for heart rate, respiration rate, movement detection, and sleep stage estimation.

- Develop robust algorithms for real-world noisy environments and validate them against reference datasets.

- Conduct feature engineering for sleep-related ML models (time/frequency/wavelet features).

- Collaborate with firmware and cloud teams to integrate algorithms into on-device and cloud pipelines.

- Contribute to internal signal quality, scoring, and annotation tools.

You Have :

- 4 - 5 years of experience in signal processing/data science/biomedical sensing.

- Solid foundation in digital signal processing (filters, FFT, IIR/FIR, wavelets).

- Experience with image models(CNN) and sequence/time series models.

- Proficiency in Python (NumPy, SciPy, mne, neurokit2, pandas, matplotlib, sckit-learn).

- Experience with sleep staging, physiological data analysis, or similar time-series modeling.

- Comfort with real-world data: noise, motion artifacts, gaps, resampling, and validation.

- (Bonus) Experience with embedded signal processing, PyTorch/TF for physiological ML, or on-device inference.