Data Scientist
Summary
Build knowledge-graph and AI-driven analytics to detect fraud and risk patterns using Python, LLMs, and graph reasoning.
Title: Data Scientist
Location: Hybrid - 3 days in office in Mexico City or Toluca
Duration: Full Time
Role Summary:
Develop advanced analytics and graph-based intelligence solutions to uncover patterns, relationships, and actionable insights for business and risk use cases.
Key Responsibilities:
- Design and implement knowledge graph models and semantic structures.
- Apply data mining techniques to detect trends, anomalies, and hidden links.
- Build data preparation, enrichment, and validation pipelines.
- Collaborate with engineering teams to produce models and graph services.
- Communicate findings clearly to technical and non-technical stakeholders.
- Ensure model/data traceability, quality, and governance alignment.
AI Skills for This Role:
- Use LLM-assisted workflows for hypothesis generation and analysis acceleration.
- Apply AI methods for graph reasoning, entity linking, and relationship discovery.
- Evaluate model outputs critically for bias, drift, leakage, and reliability.
- Use AI tools responsibly with strong data privacy and governance practices.
Required Qualifications:
- 5+ years in data science or advanced analytics.
- English proficiency: professional working level or above (B2/C1 preferred).
- Practical experience with knowledge graphs and semantic modeling.
- Strong Python skills for analytics, modeling, and experimentation.
- Solid foundation in statistics and machine learning.
- Experience with complex, high-volume, or unstructured data.
Nice to Have:
- Experience with graph databases (for example Neo4j) and NLP.
- Use cases in fraud, risk, compliance, or operational intelligence.
- Familiarity with MLOps and production model lifecycle management.
Work model: Hybrid - 3 days on-site at Client's offices in Tecnoparque (CDMX) or in Toluca