Senior Data Scientist

As a Senior Data Scientist, you will be instrumental in extracting critical insights from complex datasets, particularly focusing on temporal and geospatial features. You will develop sophisticated models to enable automation for data-driven decision-making and collaborate closely with engineering teams to translate complex data challenges into actionable solutions. The ideal candidate will possess deep expertise in advanced statistical and machine learning techniques, with a proven ability to work with unstructured and high-dimensional data, and effectively communicate findings to both technical and non-technical stakeholders.

• Design, build, and implement advanced statistical and machine learning models to extract meaningful temporal features from sequential data.
• Develop and apply sophisticated techniques to derive and utilize geospatial features.
• Implement algorithms for auto-tagging, classification, and clustering of similar data points using a combination of temporal, geospatial, and other relevant features.
• Analyze, validate, and optimize models to ensure high accuracy and performance in real-world scenarios.
• Collaborate with engineering teams to integrate models into production systems and ensure scalability.
• Visualize and communicate complex data insights, model performance, and analytical findings to cross-functional teams and stakeholders.
• Write clean, efficient, and maintainable code, adhering to best practices for data science development.

• Exceptional analytical skills with a proven ability to manipulate, analyze, and extract insights from large, complex, and high-dimensional datasets.
• Deep expertise in temporal feature extraction techniques from time-series data
• Strong understanding and practical experience with geospatial data analysis, feature engineering, and spatial reasoning.
• Proficiency in designing and implementing algorithms for classification, clustering, and feature selection.
• Expertise in machine learning algorithms, including deep learning architectures relevant to sequential and spatial data.
• Strong programming skills in Python with extensive experience in data science libraries.
• Experience with big data frameworks such as PySpark for distributed data processing.
• Excellent problem-solving skills with a meticulous focus on model validation, robustness, and accuracy.
• Ability to work independently, manage multiple priorities, and thrive in a fast-paced, collaborative environment.
• Strong communication and presentation skills, with the ability to articulate complex technical concepts to diverse audiences.

• B.S, M.S. or Ph.D. Degree in Engineering, Data Science, Computer Science, Math, Statistics, or a related quantitative field.
• 5+ years of hands-on experience as a Data Scientist with a strong focus on advanced analytics and machine learning.
• Demonstrated experience in extracting and leveraging temporal and geospatial features from large, complex datasets, including sensor and video data.
• Proven track record of developing and deploying models for classification, clustering, and/or auto-tagging in production environments.
• Extensive experience with programming languages such as Python and big data frameworks like PySpark.
• Experience working with large and complex datasets from various sources (e.g., databases, object storage).
• Track record of writing optimized, scalable, and well-documented code.

• Background in robotics, autonomous systems, or computer vision, with an understanding of perception systems and their data outputs.
• Experience with cloud platforms such as AWS or GCP, including services relevant to data storage, processing, and machine learning.
• Familiarity with data engineering principles, including building and maintaining robust data pipelines.