> Markdown version of [/jobs/ext/3584385-data-solutions-architect](https://www.wearedevelopers.com/jobs/ext/3584385-data-solutions-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Solutions Architect - **Company:** Employee-owned, Rs&h - **Location:** United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Geographic Information Systems, Artificial Intelligence, Amazon Web Services, ArcGIS (Software), Microsoft Azure, Building Information Modeling, Software as a Service, Cloud Computing, Continuous Delivery, Continuous Integration, Data Architecture, Data Governance, Data Visualization, Monitoring of Systems, Python (Programming Language), NumPy, Operational Data Store, PostGIS, Power BI, Tensorflow, SciPy, Software Deployment, SQL Databases, Tableau (Software), Visual Analytics, Google Cloud, Feature Engineering, Pytorch, Pandas, Containerization, Scikit Learn, Information Technology, Statistics Packages, Geospatial Data Abstraction Library (GDAL), Plotly, Machine Learning Operations, Drift Detection, Lidar, Raster Graphics - **Published:** October 4, 2026 - **Apply:** https://jobs.military.com/career/355936/data-solutions-architect-florida-fl-lake-city ## About the Role * Bachelor's degree in Data Science, Computer Science, Statistics, Applied Mathematics, Geography, or a related quantitative or technical discipline.\n * Fifteen (15) or more years of experience in applied data science, analytics engineering, data architecture, or a related discipline.\n * Full lifecycle experience developing data products, including concept development, requirements, architecture, model development, validation, deployment, and production support.\n * At least five (5) years of experience in client-facing consulting or professional services, including proposing, scoping, and delivering analytical solutions.\n * Current certification in a relevant technology domain or equivalent demonstrated expertise.\n * Mastery of the Python data science ecosystem, including pandas, Polars, NumPy, and SciPy.\n * Advanced proficiency in SQL and R.\n * Expert knowledge of statistical modeling and machine learning frameworks, including scikit-learn, statsmodels, PyTorch, and TensorFlow.\n * Demonstrated expertise in time-series forecasting, causal inference, feature engineering, and sampling or resampling techniques for imbalanced or sparse data.\n * Strong experience with geospatial analytics and LiDAR processing using tools such as ArcGIS, PostGIS, GeoPandas, GDAL/OGR, and PDAL.\n * Experience working with vector, raster, point-cloud, sensor, and operational data.\n * Deep experience with MLOps and model lifecycle management, including containerization, orchestration, continuous integration and delivery (CI/CD), experiment tracking, model monitoring, drift detection, and production deployment.\n * Experience deploying cloud-based solutions using Microsoft Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP).\n * Advanced proficiency in interactive data visualization and dashboard development using Power BI, Tableau, Plotly/Dash, or geospatial visualization tools.\n * Advanced knowledge of responsible AI, data governance, bias detection and mitigation, model explainability, uncertainty quantification, and statistical reliability in regulated environments.\n * Exceptional analytical and problem-solving skills.\n * Ability to communicate complex technical methods, results, limitations, and recommendations clearly to technical and non-technical stakeholders.\n, * PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Geography, or a related field.\n * Experience productizing prototypes, including software-as-a-service (SaaS) delivery and lean product incubation processes.\n * Domain experience in transportation, aviation, buildings, or construction operations.\n * Experience with traffic sensors, tolling systems, building automation systems, building information modeling (BIM), virtual design and construction (VDC), or facility telemetry.\n * Background in digital simulation environments, operational technology integration, or AI applications for infrastructure systems.\n * Familiarity with foundation model fine-tuning or multimodal modeling involving imagery, geospatial data, text, and sensor data.\n ## Related Videos - [Python Data Visualization @ Deepnote (w/ PyViz overview)](https://www.wearedevelopers.com/videos/113-python-data-visualization-deepnote-w-pyviz-overview) - [How to develop an autonomous car end-to-end: Robotic Drive and the mobility revolution](https://www.wearedevelopers.com/videos/22-how-to-develop-an-autonomous-car-end-to-end-robotic-drive-and-the-mobility-revolution) - [Vectorize all the things! 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