Senior Data Scientist: Graph ML & Entity Linking (Healthcare)

Sii Poland; Warszawa; On-site; PLN 180,000 - 320,000; Full time

Benefits offered by this job

Great place to work

Profit sharing

Centre of internal trainings

Medical care

Open and accessible management team

Job summary

Sii Poland is seeking a Senior Data Scientist to join a project building an AI-powered operating system for healthcare marketing. You will design and implement entity extraction, linking, and resolution at scale, reconciling large datasets into reliable entities and attributes for audience insights.

Responsibilities include owning the linking pipeline end-to-end, applying graph ML techniques, and ensuring data quality across sources in production-grade Python environments.

Qualifications

• 5+ years of production ML or data science experience with entity linking at scale.
• Strong Python with production-grade, tested, type-hinted code.
• SQL proficiency and experience with FastAPI, Docker, pytest, Git, and CI/CD.

Responsibilities

• Extract entities and attributes from heterogeneous sources.
• Design probabilistic entity linking and deduplication across large healthcare datasets.
• Own the linking pipeline end-to-end with scoring and calibrated probabilities.
• Define link quality metrics: precision, recall, calibration, error analysis.
• Link entities to controlled medical vocabularies for consistency.
• Use graph representations and graph ML for linking: clustering, centrality, link prediction.
• Build and maintain the data and graph estate, including ETL transformations.
• Improve algorithms to adapt to changing data sources and volumes.

Skills

Python

SQL

FastAPI

Docker

pytest

Git

CI/CD

Entity linking

Graph ML

GNNs

ETL

Data-quality monitoring

Tools

Neo4j

Amazon Neptune

Snowflake

BigQuery

Databricks

Job description

Sii Poland is seeking a Senior Data Scientist to join a project building an AI-powered operating system for healthcare marketing. You will design and implement entity extraction, linking, and resolution at scale, reconciling large datasets into reliable entities and attributes for audience insights.

Responsibilities include owning the linking pipeline end-to-end, applying graph ML techniques, and ensuring data quality across sources in production-grade Python environments.