Freelance Data Scientist with Ontology and Graph expertise
- Level
- Mid
- Work type
- Remote · Belgium only
Not stated in the posting: salary, visa.
Open. First seen 3 October 2026.
What this role asks for
Particular to this role
Neo4j · RAG · SharePoint · Test Automation · Vector Databases
Rare in adesso1's other 24 open postings.
Standard for data science / ML roles
Machine Learning · Python
Common in data science / ML postings at any company.
Read against adesso1's other open postings on this site.
The team: Freelance HIRES STEADILY
This role is one of 10 open in Freelance. 1 was posted in the last 30 days and the oldest in November: a team that hires all year rather than one being built.
WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS
CI/CD (6 of 10), SQL (6 of 10), Azure (4 of 10), GitHub (4 of 10), Agile (3 of 10), Azure DevOps (3 of 10), Git (3 of 10)
OTHER ROLES ON THIS TEAM
- Freelance Full stack .NET Developer (Angular / React) posted Oct 15
- Freelance Senior Databricks Platform Engineer posted Sep 11
- Freelance Microsoft Fabric Data Engineer posted Jun 23
- Freelance Senior Java Full-Stack Developer posted Jan 21
- Senior Business Analyst / Consultant – General Insurance posted Jan 15
- SAP S/4HANA Private Cloud / RISE Consultant posted Jan 15
- SAP S/4HANA Public Cloud Consultant posted Jan 15
- Freelance Senior Test Analyst posted Nov 19
- Senior Business Analyst / Consultant - Life Insurance posted Nov 18
From the team and dates on adesso1's own job board.
About the role
adesso Belgium is looking for a data scientist (2) to support our customer in building an AI Agent Platform Data Foundations.
Customer info:
Our customer is an international, independent provider of indirect procurement services.
Preferred start date: 1x ASAP and 1x January 2027
Duration: 12 months
Rate: depending on your location
Time Zone: CET
Your role
Build the data and context layer that powers the customer's procurement AI agent platform — canonical models, knowledge graph, semantic/taxonomy layer, and the retrieval and evaluation pipelines agents depend on. This is production infrastructure from day one, not a proof of concept: versioned, tested, and built for multiple tenants.
You will work on:
- Data products & canonical modeling — Design and deliver the first reference data products (Supplier Master, Spend Cube, Contract Register) end to end, from source ingestion through the canonical model.
- Knowledge graph & ontology — Stand up and operate the platform and working graphs (ontology, reference data, tenant separation); own the graph-plus-vector retrieval design, deciding per source whether data is represented as entities/relationships, embeddings, or both.
- Master data & semantic layer — Build matching rules, golden records, and stewardship processes for Suppliers, Contracts, and Categories; contribute to the business glossary and taxonomy-to-ontology mapping.
- Extraction & evaluation — Build document-extraction pipelines (e.g., from SharePoint sources) with confidence scoring and human review for uncertain cases; build and maintain labelled evaluation datasets and accuracy benchmarks against agreed thresholds.
- Connector framework — Build source connectors (starting with Fabric data products and master data golden records) so new sources can be onboarded without modifying the graph core or query service.
- Quality feedback loop — Implement the mechanism routing agent overrides, failures, or low-confidence retrievals back to data owners so data products improve over time rather than decay.
- Engineering practice — Work exclusively in the GitHub/Azure environment; ship via pull request with CI (build, tests, security scan, evaluation fixtures); version all schemas, connector contracts, and extraction configs.
Required Experience
Hard skills:
- Demonstrated experience taking a knowledge graph system to production (not just prototyping) — schema design, query performance, tenant/data isolation - Using Neo4J and Python
- Strong background in semantic modeling: ontologies, taxonomies, business glossaries, and their relationship to graph and canonical data models.
- Hands-on experience with semantic web standards and technologies including OWL/OWL2, RDF, RDFS, SPARQL, ontology lifecycle management, taxonomy alignment, and semantic reasoning.
- Experience building data products and master-data pipelines (entity matching, golden-record consolidation, stewardship workflows).
- Experience designing and implementing hybrid retrieval architectures combining graph databases (e.g., Neo4j) and vector databases to support semantic search, RAG, and AI agent workloads.
- Experience with retrieval architectures combining graph and vector/embedding approaches.
- Experience building and maintaining labelled evaluation datasets and measuring extraction/model accuracy against a threshold.
- Proficiency with modern data/ML engineering practices: version control, CI/CD, automated testing, containerized deployment
- Experience with Microsoft Fabric and SharePoint-based document extraction pipelines.
Soft skills:
- Fluent in ENG
- Open to travelling if needed (EU), this position is fully remote
- Collaborative mindset, ideally with a proven similar work experience
Why join adesso Belgium?
- Work in an international group with strong local expertise in Belgium.
- Collaborate with cross-functional teams to deliver trusted, compliant, reusable data products.
- Flexible freelance setup with the support of a growing adesso Belgium community.
See Data Scientist salaries in Remote →
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