Geospatial Data Scientist / Machine Learning Engineer

About the role

AKTEK Inc, a SaaS and intelligence-as-a-service provider serving public and private clients worldwide, is looking for a Geospatial Data Scientist / Machine Learning Engineer to join its globally distributed team. The role focuses on building algorithms that detect security anomalies in geospatial data, using large-scale datasets to identify threats and risks.

Key responsibilities

• Research, design and develop algorithms for detecting security anomalies in geospatial data, identifying potential threats and risks.
• Apply statistical modelling, machine learning and spatial analysis to find security-related patterns and outliers in large geospatial datasets.
• Clean, preprocess and integrate geospatial data from diverse sources, prioritising data quality and integrity.
• Implement scalable, efficient algorithms to handle big geospatial data (trillions of data points available for training).
• Work with cross-functional teams to understand project requirements and ensure technical solutions address security concerns.
• Integrate security detection algorithms into AKTEK iO and AKTEK iQ with the development team.
• Use cloud technologies for data and machine learning product development, including data wrangling, assimilation and standardisation in production.
• Use code versioning, automation and workflow orchestration tools such as GitHub, and follow data warehousing concepts in AWS or similar platforms.
• Debug, document and write structured code, and explain technical and business solutions clearly.

Required profile

• Academic background in a technical field, computer science or engineering, or equivalent.
• Strong background in data science, machine learning and geospatial analytics.
• Demonstrated expertise in anomaly detection algorithms, preferably on geospatial data.
• Experience with large datasets and scalable algorithms.
• Strong English and ability to work with remote teams across time zones (GMT-4, GMT+2); autonomous and analytical.
• Strong plus: business intelligence experience, startup experience, and fluency in a foreign language.

Required skills

• Python and geospatial libraries such as GeoPandas and Shapely
• Machine learning frameworks such as scikit-learn and PyTorch
• APIs including Google Maps, OpenStreetMap, ArcGIS and LLM APIs
• GIS tools such as QGIS, ArcGIS and Google Earth, and formats like KML/KMZ, GeoJSON and shapefiles
• AWS cloud services

What we offer

• A fair compensation package, including 37 vacation days.
• High work flexibility and a remote-friendly setup.
• A flat, technically dense team with broad ownership and real architectural influence.