Data Scientist

Veriipro; Dallas (TX); On-site; USD 140,000 - 200,000; Full time

Job summary

Veriipro in Dallas, TX seeks an accomplished data scientist with 10+ years in applied data science, analytics engineering, and systems modeling to design advanced machine learning solutions for complex business problems.

You will build predictive models and time-series forecasts, perform feature engineering on large geospatial datasets, and mentor teams while partnering with stakeholders to deliver insights and scalable AI deployments.

Qualifications

• 10+ years in applied data science, analytics engineering and systems modeling.
• 5+ years of client-facing or consulting experience delivering analytics solutions.
• Expertise in statistical modeling, ML, and predictive analytics.
• Proficiency with Python and ML frameworks (scikit-learn, PyTorch, TensorFlow).
• Experience with time-series forecasting, causal inference and advanced sampling.
• Geospatial analytics and LiDAR data processing expertise.
• Hands-on with ArcGIS, PostGIS, GeoPandas, GDAL/OGR, PDAL and related libraries.
• Experience with vector, raster, point-cloud, and sensor datasets.
• Excellent analytical, communication and stakeholder management skills.

Responsibilities

• Design and develop advanced ML and statistical models for business problems.
• Build predictive models and time-series forecasts; apply causal inference frameworks.
• Perform feature engineering and data preparation on large-scale datasets.
• Develop geospatial analytics and LiDAR processing solutions using standard tools.
• Analyze diverse geospatial data to generate actionable insights.
• Partner with stakeholders to scope and deliver data science solutions.
• Present analytical findings to technical and business audiences.
• Optimize model performance, scalability and deployment in production.
• Mentor data scientists and promote best practices in analytics and ML.
• Support innovation initiatives with AI-driven solutions.

Skills

Applied Data Science

Analytics Engineering

Systems Modeling

Client-facing experience

Statistical modeling

Machine learning

Predictive analytics

Time-series forecasting

Causal inference

Geospatial analytics

Data storytelling

Tools

ArcGIS

PostGIS

GeoPandas

GDAL/OGR

PDAL

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.