Data Scientist - W2

Hi, Data Scientist / Analytics Engineer Location: Temple Terrace, FL; Irving, TX; Basking Ridge, NJ; or Ashburn, VA JD: We are seeking a highly skilled and results-driven Data Scientist / Analytics Engineer to join our Data Science Development team within Network Planning.

In this role, you will be responsible for the core modernization, evolution, and scaling of our geospatial and statistical fiber modeling platforms, specifically our proprietary automated routing, network optimization, and Feeder Distribution Hub (FDH) modeling engines.

You will be responsible for architecting and unifying complex network routing engines, scaling high-throughput geospatial datasets, optimizing cloud database performance, and delivering high-impact spatial analytics that directly guide our national broadband infrastructure strategy.

Key Responsibilities - Design, build, and optimize spatial routing and network planning models across our core automated planning platforms and fiber mapping engines. Drive the strategic software convergence of legacy spatial planning scripts into a unified, high-performance network modeling stack.

Execute large-scale Feeder Distribution Hub (FDH) and Fiber-to-the-Home (FTTH) remodeling using Djikstra, Kruskal or other minimum tree spanning algorithms utilizing network topology, and spatial datasets. Transition and standardize spatial graph processing and routing engines Ability to handle large datasets in spatial data formats (e.g., shapefiles, GeoJSON).

Integrate advanced spatial datasets (open street maps, enterprise address databases, and master location repositories) into automated ETL pipelines for high-accuracy routing and spatial analysis. Oversee production relational and columnar databases across cloud environments.

Lead continuous database optimization initiatives automating table maintenance, rebuilding high-traffic spatial reference cross-reference tables, and tuning long-running queries to maintain low latency. Build and manage automated workflow pipelines (e.g., Airflow/Python) to streamline real-time data sharing across cross-functional engineering, analytics, and AI teams.

Implement self-healing scripts, system telemetry monitoring, and strict role-based access security across the modeling stack. Architect secure, scalable, and cost-effective data infrastructure environments across multi-cloud environments (AWS and GCP).

Minimum Qualifications

• Bachelor or master’s degree in computer science, Data Science, Geographic Information Systems (GIS), Operations Research, Software Engineering, or a related quantitative field.
• Experience: 5+ years of experience in data engineering, geospatial analytics, or data science roles, with demonstrated leadership in technical delivery.

Core Languages / Web Frameworks

Proficiency in Python (3.x), SQL, and microservices/web execution frameworks (Flask, FastAPI, or Django) a must.

Spatial GIS Mastery

Deep expertise with spatial analytics tools, spatial SQL, PostGIS, ESRI/ArcGIS frameworks, and open-source mapping platforms (e.g., Overture Maps, QGIS, PG Tile Server).Database Systems: Demonstrated experience with transactional and analytics databases (PostgreSQL, Oracle, Redshift, BigQuery).Workflow Automation & Cloud: Hands-on experience with Apache Airflow, Docker, AWS (EC2/RDS), and GCP (BigQuery, Cloud Storage).

Preferred Qualifications :Direct experience in telecommunications network planning, fiber infrastructure deployment (FTTH, FWA), or complex graph/network routing algorithms. Proven track record of system performance tuning, query optimization, and cost-reduction initiatives across enterprise cloud environments.

Key Competencies Technical Ownership

Strong ownership mindset with a track record of driving complex engineering projects from inception to production deployment.

Collaborative Leadership

Ability to work cross-functionally across Network Planning, IT, Network Operations, and Executive Analytics teams.

Problem Solving

Exceptional analytical skills to diagnose performance bottlenecks in large-scale spatial modeling environments. Category Name Required Importance Experience Analytics Data Science Yes 1 Continuous Automation Testing GIS Yes 1 Best regards, Shivani Gaur [email protected]