Senior Applied Scientist | Motion Sensing, DSP & ML

Quin; Hyderabad; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Quin is seeking an Applied Data Scientist in Hyderabad to work on advanced sensor data analytics, focusing on building intelligent models to extract insights from high-frequency data. Candidates should have a strong background in Digital Signal Processing, machine learning, and IMU data analysis.

The successful applicant will be responsible for collaborating with engineering teams to develop algorithms and processes to enhance motion-based systems.

Qualifications

• Strong expertise in Digital Signal Processing (DSP).
• Experience with machine learning for time-series data.
• Hands-on experience with motion sensor data analysis.
• Experience in GPS data and geospatial analysis.
• Strong proficiency in Python and data analysis tools.

Responsibilities

• Analyze large-scale, real-time sensor datasets.
• Design and develop machine learning models for motion analysis.
• Apply Digital Signal Processing techniques for signal conditioning.
• Work closely with Motion Algorithms Engineers.
• Define and execute data collection strategies.

Skills

Digital Signal Processing (DSP)

Machine learning for time-series data

IMU and motion sensor data analysis

GPS data and geospatial analysis

Python (NumPy, SciPy, Pandas)

Data analysis and modeling tools

Statistics and probability

Linear algebra

Signal processing

Education

Master's degree in Computer Science, Engineering, or related field

Tools

Data visualization tools

Real-time data systems

Kalman filters

Job description

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.

Location

Hyderabad

Experience

4–8 years

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