Senior Geospatial Data Scientist – Address, Geocoding
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Job Description
Senior geospatial data scientist advancing Cotality’s US property geocoding and address intelligence products. Improving address parsing, spatial precision, validation, and data quality through Python, SQL, and geospatial technologies.
Responsibilities:
- Advance Cotality’s flagship enterprise geocoding product supporting property and location intelligence products
- Build robust systems for complex US addressing scenarios
- Develop mechanisms to improve geolocation precision from areal to parcel, rooftop, front-door, loading-dock, and drop-off-point levels
- Develop spatial validation loops using contributor data and terrestrial datasets
- Evaluate and benchmark third-party geocoding services against in-house solutions
- Evolve automated confidence-scoring frameworks for addressing and geocoding data quality
- Implement enhancements to improve geocoding accuracy, explainability, and currency
- Conduct hands-on experiments with open-source, cloud-native geospatial tools
- Collaborate with engineering to take features from ideation through production
- Evaluate data vendors with the in-house data acquisition team
- Drive internal and external awareness of address hygiene
Requirements:
- Mastery of USPS CASS/NCOA processes, TIGER data, and nuances of the US postal system
- Experience working with commercial and publicly available road network datasets
- Knowledge of US land parcel data and its relationship to addresses
- Knowledge of Census data
- 5+ years of relevant experience
- Ability to prototype and demonstrate ideas through hands-on coding in a Jupyter notebook-oriented environment
- Python and SQL coding skills
- Experience with geospatial, address, and routing-focused Python libraries
- Experience with GeoPandas, Shapely, Proj, Kepler/Pydeck, Libpostal, and Valhalla
- Knowledge of spatial data formats including shapefiles, GeoJSON, GeoParquet, and FGB
- PostGIS spatial SQL
- GDAL command-line tools
- QGIS
- Working knowledge of REST APIs, JSON structures, and Postman
- Statistics fundamentals
- Bachelor's degree or equivalent work history (nice to have)
- Some experience with Apache Spark or another Big Data stack (nice to have)
- Experience with cloud-based spatial analytics platforms such as Carto (nice to have)
- Geospatial pattern matching/recognition algorithms (nice to have)
Benefits:
- Generous PTO and 11 paid holidays
- Well-being and volunteer time off
- Up to 16 weeks of fully paid parental leave
- Baby stipend
- Multiple medical plan options
- Mental health and wellness support offerings
- 401(k) with company match and vesting after one year
- $400 annual well-being stipend
- Tuition assistance up to $5,250
- Recognition Rewards
- Referral bonuses
- Exclusive discounts
- Flexible working model
- Competitive salary and benefits package
- Professional growth opportunities
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