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# Senior Data Scientist

- **Company:** TECHNIFY INC
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $80,000.0
- **Contract:** Permanent contract
- **Skills:** Geographic Information Systems, Data Analysis, Big Data, Python (Programming Language), Machine Learning, Sensor Fusion, Spatial Data Infrastructures, Feature Engineering, Uncertainty Quantification (UQ), Geospatial Data Abstraction Library (GDAL), Machine Learning Operations
- **Published:** October 9, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pqelj1t6jv

## About the Role

* Strong background in applied statistics, spatial data science, or a related quantitative field
 * Experience working with Python; geospatial libraries (GeoPandas, GDAL, Rasterio etc.) are a plus but not essential
 * Solid understanding of statistical modelling and uncertainty quantification, e.g. Bayesian methods, Kalman or particle filtering
 * Experience working with complex or large-scale datasets
 * Ability to work in a cross-functional engineering environment
 * Experience deploying models into production systems

## Description

You'll be working as part of a newly formed data science team, focusing on spatial analytics and multi-sensor data fusion.

This role sits at the intersection of applied statistics, machine learning, geospatial data, and mathematical modelling, with a strong emphasis on solving real-world problems, particularly around quantifying and managing uncertainty across multiple data sources.

What You'll Be Doing

 * Developing algorithms for spatial data correlation and fusion
 * Analysing and integrating multi-sensor datasets
 * Applying statistical techniques (Bayesian methods, Kalman/particle filtering, and other uncertainty quantification approaches) to improve predictions and manage uncertainty across data sources
 * Building machine learning models for classification, regression, and tracking
 * Performing feature engineering and dimensionality reduction on spatial data
 * Building tools to visualise and validate model outputs
 * Working closely with engineers to deploy models into production systems