B2B Data Scientist

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🕒 June 8

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RecruityTalent

WebsiteLinkedInAll Job Openings

1 - 10 employees

Founded 2024

💼 Consulting

📦 Logistics

🎯 Recruiter

Consulting • Logistics • Recruitment

RecruityTalent is a recruitment agency that partners with companies to manage the full hiring lifecycle, offering standard and flexible solutions through onsite recruitment projects and agency services. It provides end-to-end hiring support — including job postings, candidate sourcing, screening, interviews and offer management — with experience in IT, BPO and executive search, aligning hiring to clients' business vision and company culture.

📋 Description

• Design and deliver reference data products, including Supplier Master, Spend Cube, and Contract Register, from source ingestion through canonical modeling • Establish and operate knowledge graphs, ontologies, reference data, and tenant separation • Design graph-plus-vector retrieval approaches for different data sources • Build matching rules, golden records, and stewardship processes for Suppliers, Contracts, and Categories • Contribute to the business glossary and taxonomy-to-ontology mapping • Build document-extraction pipelines with confidence scoring and human review workflows • Maintain labeled evaluation datasets, accuracy benchmarks, and threshold-based evaluations • Build source connectors beginning with Fabric data products and master data golden records • Implement feedback loops routing agent overrides, failures, and low-confidence retrievals to data owners • Work in the company GitHub/Azure environment and ship through pull requests with CI, testing, security scans, and evaluation fixtures • Version schemas, connector contracts, and extraction configurations

🎯 Requirements

• Demonstrated experience taking a knowledge graph system to production, including schema design, query performance, and tenant/data isolation • Experience using Neo4J and Python • Strong background in semantic modeling, including ontologies, taxonomies, business glossaries, graph models, and canonical data models • Hands-on experience with OWL/OWL2, RDF, RDFS, SPARQL, ontology lifecycle management, taxonomy alignment, and semantic reasoning • Experience building data products and master-data pipelines, including entity matching, golden-record consolidation, and stewardship workflows • Experience designing and implementing hybrid retrieval architectures combining graph databases and vector databases for semantic search, RAG, and AI agent workloads • Experience building and maintaining labeled evaluation datasets and measuring extraction/model accuracy against thresholds • Proficiency with version control, CI/CD, automated testing, and containerized deployment • Preferred: experience with Python and Neo4J • Preferred: experience with enterprise ontologies, OWL/RDF/RDFS, SPARQL, taxonomy management, semantic reasoning, knowledge graph architectures, ontology editors such as Protégé, graph and vector databases, reasoning engines, linked-data architectures, Microsoft Fabric, SharePoint extraction pipelines, and auditability/explainability systems

🏖️ Benefits

• GDPR-compliant handling of candidate information • Secure storage and management of candidate information in accordance with local GDPR regulations