Minimum Qualifications:
Education
Master s degree in Data Science, Computer Science, Statistics, Applied Mathematics, Geography, or a related quantitative field with 5 years experience.
Bachelor s degree and 10 years experience in Lieu of Masters.
Experience
Typically requires 10 years of hands-on experience in applied data science, analytics engineering, and systems modeling.
Minimum of 5 years in client-facing, consulting, or business development roles where analytic solutions were proposed, scoped, and delivered.
License/Certification
None required at time of hiring.
Knowledge, Skills, and Abilities (KSAs)
Mastery of the full Python data science ecosystem (pandas, Polars, NumPy, SciPy), advanced SQL, and R.
Expert proficiency in statistical modeling and machine learning frameworks (scikit-learn, statsmodels, PyTorch, TensorFlow) including time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques for imbalanced or sparse infrastructure data.
Strong expertise in geospatial analytics and LiDAR processing using ArcGIS, PostGIS, GeoPandas, GDAL/OGR, PDAL, and related libraries for vector, raster, point-cloud, and sensor data.
Deep MLOps and model lifecycle experience: containerization, orchestration, CI/CD pipelines, experiment tracking, model monitoring, drift detection, and production deployment on Azure, AWS, or Google Cloud Platform.
Proficiency in developing and operationalizing advanced interactive visualizations and dashboards using Power BI, Tableau, Plotly/Dash, and geospatial visualization tools.
Advanced knowledge of responsible AI, data governance, bias detection/mitigation, model explainability, uncertainty quantification, and statistical precision and reliability in regulated environments.
Exceptional analytical problem-solving skills and the ability to clearly communicate complex methods, results, limitations, and recommendations to both technical teams and non-technical stakeholders.
** strong Power BI Experience**
Preferred Qualifications:
Domain experience in transportation, aviation, buildings, or construction operations (e.g., traffic sensors, tolling, BAS/BMS, BIM/VDC, facility telemetry).
Background in digital simulation environments, operational technology integration, or AI applied to infrastructure systems.
Familiarity with foundation model fine-tuning or multimodal modeling (imagery, geospatial, text, sensor data).
Prior experience with lean product incubation or innovation processes.
Never miss an opportunity! Create an alert based on the job you applied for.
