Data Scientist - Mc Lean - Avineon

Description

Avineon is seeking a Data Scientist to add to our team. The Data Scientist will develop and deploy machine learning models for spatiotemporal data analysis using Python APIs and geospatial software platforms.
Duties and Responsibilities:

• Design and implement geospatial analysis workflows to extract insights from complex location-based datasets.
• Build predictive models that incorporate temporal patterns and spatial relationships in large-scale geospatial data.
• Create interactive maps, visualizations, and dashboards to communicate analytical findings to stakeholders.
• Research and implement cutting-edge techniques in spatiotemporal machine learning, including time series forecasting, spatial clustering, and geographic pattern recognition.
• Optimize model performance and scalability for processing large geospatial datasets in production environments.
• Work closely with product managers and clients to translate business requirements into technical solutions.
• Collaborate with cross-functional teams to identify data requirements and improve analytical workflows.
• Mentor junior team members and contribute to best practices for spatiotemporal data science workflows.

Education and Experience Requirements:

• Master's degree in Data Science, Computer Science, Geography, Mathematics, Statistics, or related quantitative field.
• Two to four years of experience in data science or machine learning with demonstrable expertise in geospatial analysis.
• Strong proficiency in Python with experience in scientific computing libraries (NumPy, Pandas, Scikit-learn, SciPy).
• Hands-on experience with geospatial Python libraries such as GDAL, GeoPandas, Shapely, Rasterio, Folium, or similar.
• Solid understanding of machine learning algorithms, statistical modeling, and time series analysis.
• Experience with geospatial data formats (GeoJSON, Shapefiles, GeoTIFF, NetCDF) and coordinate reference systems.
• Proficiency in SQL and experience working with spatial databases (PostGIS preferred).
• Experience with version control systems (Git) and collaborative development workflows.
• Strong problem-solving skills and ability to work independently on complex analytical challenges.
• Excellent communication skills with ability to present technical findings to both technical and non-technical audiences.

Preferred Qualifications:

• Experience working within the U.S, Department of Defense and intelligence community.
• Knowledge of and experience working with standards set by the Geospatial-Intelligence (GEOINT) Standards Working Group (GWG)
• Experience working with DoDAF Formal Ontology (DM2).
• Experience working within MARS framework.
• Experience working with NATO Interoperability Standards and Profiles (NISP)
• Five plus years of experience in data science with focus on spatiotemporal analytics.
• Experience with deep learning frameworks (TensorFlow, PyTorch) applied to spatiotemporal problems.
• Knowledge of remote sensing data analysis and satellite imagery processing.
• Experience with cloud platforms (AWS, GCP, Azure) and distributed computing frameworks (Spark, Dask).
• Experience with graph neural networks or other advanced machine learning techniques for spatial data.
• Knowledge of cartographic principles and advanced mapping techniques.
• Background in GIS software (QGIS, ArcGIS) and spatial analysis techniques.

Security Clearance Requirement:

• Must hold an active Top Secret clearance with SCI eligibility.

Work Location:

• Washington, DC area is preferred, but open to other locations.

Avineon Benefits Overview (for full-time employees)

• Medical
• Dental
• Vision
• Flexible Spending Account (FSA)
• Paid Holidays
• Paid Time Off (includes vacation and sick time)
• Fitness Membership Reimbursement Program
• Tuition Reimbursement Program
• 401(k) & Employer Match
• Long-Term Disability and Short-Term Disability (Employer Paid)
• Basic Term Life and AD&D (Employer Paid)
• Voluntary Term Life and AD&D
• Career Growth Planning
• Job Related Certification Program (Employer Paid)