Senior Applied Scientist | Motion Sensing, DSP & ML

Senior Applied Scientist | Motion Sensing, DSP & ML

Location:

Experience:

Job Overview

Key Responsibilities

• Analyze large-scale, real-time sensor datasets from:
  • Accelerometers
  • Gyroscopes
  • IMUs and other motion sensors
  • GPS and location systems
• Design and develop machine learning models for:
  • Motion analysis and classification
  • Event detection (crash, fall, slip, impact, etc.)
  • Behavioral and activity pattern recognition
• Digital Signal Processing (DSP) techniques for:
  • Signal conditioning and noise reduction
  • Feature extraction from time-series data
• Work closely with Motion Algorithms Engineers to:
  • Develop and refine sensor fusion algorithms
  • Improve GPS filtering and map matching techniques
• Define and execute data collection strategies:
  • Ensure high-quality labeled datasets
  • Work with app/firmware teams to capture relevant signals
• Perform feature engineering and feature analysis for model performance optimization
• Build and maintain data pipelines and processing workflows for:
  • Data ingestion
  • Cleaning and preprocessing
  • Model training and evaluation
• Contribute to dashboarding and monitoring systems to track:
  • Data health
  • Model performance
  • Anomalies and edge cases
• Analyze user, sensor, and system data to generate:
  • Actionable insights
  • Usage patterns
  • Algorithm improvement opportunities

R&D and Innovation Responsibilities

• Lead research and development for new motion-based features and detection systems
• Explore and implement novel approaches for:
  • Crash detection
  • Event classification
  • Sensor-based intelligence
• Collaborate on data architecture design with Motion Algorithms Engineers
• Conduct deep data analysis for feature discovery and validation
• Write technical documentation, white papers, and research reports
• Contribute to intellectual property (IP) development:
  • Patent drafting
  • Novel algorithm design

Required Skills & Qualifications

• Strong expertise in Digital Signal Processing (DSP)
• Strong experience in machine learning for time-series data
• Hands-on experience with IMU and motion sensor data analysis
• Experience working with GPS data and geospatial analysis
• Strong proficiency in:
  • Python (NumPy, SciPy, Pandas, ML libraries)
  • Data analysis and modeling tools
• Strong foundation in:
  • Statistics and probability
  • Linear algebra
  • Signal processing
• Good understanding of physics (mechanics, motion dynamics)
• Experience with feature engineering and model evaluation

Preferred Qualifications

• Experience with deep learning for time-series data (LSTM, Transformers, etc.)
• Familiarity with sensor fusion techniques (Kalman filters, etc.)
• Experience working with real-time or streaming data systems
• Exposure to data visualization and dashboarding tools
• Familiarity with embedded systems constraints
• Experience in wearables, mobility, or safety systems
• Experience in sports analytics or mobility platforms
• Prior work in crash detection, biomechanics, or safety systems
• Experience in end-to-end ML lifecycle

Soft Skills

• Strong analytical and research mindset
• Ability to translate raw data into meaningful insights and models
• Excellent collaboration across algorithm, firmware, and hardware teams
• Strong documentation and communication skills

Cross-Functional Collaboration

• Partner with Motion Algorithms Engineers to co-develop algorithms and data pipelines
• Work with Firmware Engineers to ensure high-quality data capture and labeling
• Collaborate with Hardware Engineers to understand sensor characteristics and limitations
• Support product and backend teams with insights, metrics, and data-driven decisions

Key Priority Requirements

1. Expertise in Motion data analysis - GPS, Accelerometers, Gyroscopes, etc.
2. Expertise in Digital Signal Processing - Filtering on data
3. Expertise in ML Model development on Motion data
4. Expertise in Physics and Mathematical Modelling of Events