Data Scientist

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.