Applied Mathematician for Geospatial Data Architecture — Graph Theory & Discrete Mathematics
Budget: $5.0 - $15.0
HOURLY / PART_TIME
⭐ 4.97 (4)
Canada
probability-theory, mathematics, python, data-science
Preferred qualifications
- Experience: Intermediate
We are developing a Canadian geospatial intelligence system that will organize millions of geographic, economic, real estate, infrastructure, and institutional records.
The system will use approximately 900,000 Canadian postal codes as a geographic indexing layer, connecting them with:
10+ million property addresses
Municipalities, provinces, and territories
Businesses and government organizations
Schools, universities, and healthcare facilities
Infrastructure assets and projects
Indigenous communities
Census, economic, and real estate data
The long-term objective is to enter any Canadian postal code and generate a structured profile of the surrounding area, including nearby institutions, infrastructure, businesses, demographic characteristics, economic indicators, and real estate information.
We are seeking an applied mathematician to help design the system from first principles using discrete mathematics, graph theory, set theory, relational structures, and practical data-modeling concepts.
This is initially an architecture and research assignment—not a large software-development contract.
Core Questions
The selected mathematician will evaluate:
Whether the system should be represented primarily as a graph, hierarchy, relational model, interconnected graphs, or hybrid architecture.
The major mathematical sets and entities within the system.
Appropriate node types, edge types, directions, weights, and relationship rules.
How geographic hierarchies and overlapping boundaries should be represented.
How permanent identifiers should be assigned to millions of objects.
Which mathematical concepts and algorithms will be most useful as the system develops.
How new datasets can be added without redesigning the underlying architecture.
How the theoretical model should translate into practical database implementation.
Potentially relevant concepts include:
Graph traversal
Clustering and community detection
Connected components
Centrality
Nearest-neighbour analysis
Shortest paths
Spatial relationships
Bipartite and multilayer graphs
Set membership
Matching and optimization
Hierarchical and overlapping classifications
Temporal graphs and changing relationships
Initial Deliverable
Please provide a concise architecture report containing:
Recommended mathematical architecture
Identification of major sets and entity types
Proposed node and edge structure
Recommended geographic hierarchy
Identifier strategy
Relevant algorithms and mathematical concepts
A conceptual entity-relationship or graph diagram
Practical implementation recommendations
Recommended first proof of concept
Important assumptions, risks, and common modeling mistakes
The report should explain the recommendations in plain English while referencing graph theory and discrete mathematics where appropriate.
A strong initial engagement may lead to additional paid work designing individual models, reviewing implementations, and supporting the system’s development.
Ideal Background
We are particularly interested in candidates with experience in one or more of the following:
Applied mathematics
Discrete mathematics
Graph theory
Network science
Operations research
Mathematical modeling
Computational geometry
Geographic or spatial networks
Knowledge graphs
Relational database modeling
Python, NetworkX, SQL, or PostgreSQL/PostGIS
A mathematics student, graduate student, researcher, or experienced independent mathematician may be suitable. Formal GIS experience is helpful but not mandatory. The ability to translate mathematical ideas into a scalable and understandable system is more important than knowing a particular software platform.
Application Questions
Please answer the following:
How would you initially represent a system connecting properties, postal codes, municipalities, institutions, infrastructure, and businesses?
Would you recommend a relational database, graph database, or hybrid architecture? Why?
Describe one real-world network or data architecture you have previously modeled.
Have you implemented graph algorithms in Python, NetworkX, SQL, or another programming environment?
How would you distinguish genuine geographic hierarchy from overlapping geographic relationships?
What would you include in the first proof of concept?
Please provide an example of previous mathematical modeling, graph theory, or data-architecture work.
Please begin your application with the words “Geospatial Graph” so we know you have read the complete posting.
Project Structure
Initial 3 Five Hour Consultants to Determine Appropriate Approach
Expected timeline: approximately 1–2 weeks
Potential for continuing project-based work
Clear written communication required
All work must be original and practically applicable
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