Job Description

Required Skills

• 10+ years of hands-on experience in Applied Data Science, Analytics Engineering, and Systems Modeling.
• 5+ years of client-facing, consulting, or business development experience delivering analytics solutions.
• Expertise in statistical modeling, machine learning, and predictive analytics.
• Strong proficiency with Python, scikit-learn, statsmodels, PyTorch, and TensorFlow.
• Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques.
• Strong expertise in geospatial analytics and LiDAR data processing.
• Hands-on experience with ArcGIS, PostGIS, GeoPandas, GDAL/OGR, PDAL, and related geospatial libraries.
• Experience working with vector, raster, point-cloud, and sensor datasets.
• Excellent analytical, communication, and stakeholder management skills.

Roles & Responsibilities

• Design and develop advanced machine learning and statistical models to solve complex business problems.
• Build predictive models, time-series forecasting solutions, and causal inference frameworks.
• Perform feature engineering, data preparation, and advanced sampling techniques for large-scale datasets.
• Develop geospatial analytics and LiDAR processing solutions using industry-standard tools and libraries.
• Analyze vector, raster, point-cloud, and sensor data to generate actionable insights.
• Partner with business stakeholders to scope, design, and deliver data science solutions.
• Present analytical findings and recommendations to technical and business audiences.
• Optimize model performance, scalability, and deployment in production environments.
• Mentor data scientists and promote best practices in analytics and machine learning.
• Support innovation initiatives through advanced analytics and AI-driven solutions.

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