Senior Applied Scientist | Motion Sensing, DSP & ML
Location:
Hyderabad
Experience:
4–8 years
Job Overview
We are looking for a highly analytical and research-driven
Applied Data Scientist
with deep expertise in
Digital Signal Processing (DSP)
,
machine learning
, and
sensor data analytics
. This role focuses on building intelligent models and extracting insights from high-frequency motion and GPS data, enabling advanced features for safety, activity tracking, and event detection.
You will work closely with Motion Algorithms, Firmware, and Hardware teams to transform raw sensor data into robust, production-ready intelligence and drive innovation in motion-based systems.
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
Apply
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
Expertise in Motion data analysis - GPS, Accelerometers, Gyroscopes, etc.
Expertise in Digital Signal Processing - Filtering on data
Expertise in ML Model development on Motion data
Expertise in Physics and Mathematical Modelling of Events
