Data Scientist
3 weeks ago
Experience: 6+ Years
Location: Remote
Contract Duration: Short Term
Work Time: IST Shift
Job Description
We are seeking an experienced Data Scientist with over 6 years of expertise in analyzing large-scale, real-world datasets, particularly from autonomous fleets, commercial trucks, or connected vehicles. The candidate should be adept in analytical thinking, modeling, and applying machine learning to derive actionable insights from multi-modal vehicular data.
Roles and Responsibilities
• Analyze high-volume sensor and telemetry data (GPS, CAN, LiDAR, camera, IMU, radar) from truck fleets
• Build machine learning and statistical models for anomaly detection, failure prediction, routing optimization, and driver behavior analysis
• Collaborate with cross-functional teams to enhance autonomy performance and operational efficiency
• Develop pipelines for cleaning, processing, and transforming structured and unstructured vehicle data
• Apply time-series analysis, clustering, and predictive modeling on vehicle and driving patterns
• Create dashboards and tools for data visualization aimed at business and product decision-making
• Translate complex data findings into clear and actionable business and engineering insights
Required Skills and Qualifications
• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or related field
• Minimum 6 years of hands-on experience in data science and analytics
• Proficient in Python and libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch
• Experience with big data platforms like Spark and cloud services (AWS/GCP)
• Strong knowledge in time-series data, signal processing, and spatiotemporal machine learning
• Experience working with connected vehicle data or autonomous truck telemetry
• Familiarity with vehicle dynamics, CAN data decoding, or driver behavior modeling
• Skilled in SQL and data visualization tools (Tableau, PowerBI, Plotly)
Preferred Skills
• Hands-on experience with deep learning frameworks (PyTorch, TensorFlow)
• Expertise in time-series or geospatial data analysis
• Exposure to big data tools such as Spark, Hadoop, and NoSQL databases
• Experience with Docker, CI/CD, and version control tools
• Background in autonomous systems, IoT, or mobility analytics
• Knowledge of autonomous driving stacks and sensor fusion
• Familiarity with edge AI deployment or model compression techniques
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