Job Description

:

Role Overview:

We are seeking a highly skilled

GIS Engineer / Data Scientist

with hands-on experience in

QGIS

,

Esri ArcGIS

, and

Python

to support geospatial data analysis, visualization, and business decision-making. The role bridges the gap between geospatial technology and business analytics -- leveraging spatial data to deliver actionable insights and data-driven recommendations.

Key Responsibilities:

Design, manage, and analyze geospatial datasets using

QGIS

and

Esri ArcGIS

tools. Perform

spatial and statistical analysis

to identify trends, patterns, and correlations across geographical data. Develop

Python-based data pipelines

, scripts, and automation for data cleaning, geoprocessing, and spatial modeling. Integrate GIS data with

business intelligence

,

data science

, and

analytics platforms

(e.g., Power BI, Tableau, Pandas, NumPy). Support business teams with

map-based insights

, dashboards, and geospatial visualizations. Work with large, multi-source datasets including shapefiles, GeoJSON, WMS/WFS, APIs, and satellite data. Collaborate with cross-functional teams (Data Engineering, Business, and Product) to define geospatial use cases and data-driven strategies. Present analytical outcomes and recommendations to stakeholders using clear visual and narrative storytelling. Ensure data quality, consistency, and standardization across geospatial datasets.

Required Skills and Qualifications:

Bachelor's or Master's degree in

Geoinformatics, Geography, Computer Science, Data Science, Statistics

, or related field. Strong hands-on experience with

QGIS

and

Esri ArcGIS

(ArcGIS Desktop, ArcGIS Pro, ArcGIS Online). Proficiency in

Python

(Pandas, NumPy, GeoPandas, Shapely, ArcPy, or PyQGIS). Good understanding of

geospatial analysis

,

coordinate systems

, and

spatial joins/intersections

. Strong analytical, statistical, and problem-solving skills. Experience integrating GIS with

Power BI

or

dashboards

for visual analytics. Familiarity with

machine learning

or

predictive modeling

using Python (scikit-learn, XGBoost).
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