Data Scientist

What we’re looking for:
● Strong experience applying AI/ML to healthcare data and clinical problems.
● Hands-on with medical datasets (clinical / EHR, imaging, labs, or registries) and their real-world pitfalls.
● Solid understanding of clinical workflows and how models fit into care.
● Rigorous model validation: study design, metrics, bias, generalization, and clinical safety.
● Discipline around reproducibility, documentation, and data governance.
Technical skill stack:
The tools and technologies you should be strong in. We don’t expect every single item — depth in the core stack matters most.
● Programming: Python (expert) and SQL; R a plus
● ML & deep learning: scikit-learn, PyTorch, TensorFlow / Keras, XGBoost / LightGBM
● Data engineering: pandas, NumPy, Polars, SciPy, statsmodels; reproducible pipelines
● Clinical NLP: Hugging Face Transformers, spaCy / scispaCy, cTAKES or MedCAT for clinical text
● Medical imaging (role-dependent): MONAI, SimpleITK, pydicom, nibabel, OpenCV
● Healthcare data standards: FHIR, HL7, DICOM, OMOP CDM; ICD, SNOMED CT, and LOINC coding
● Statistics & validation: biostatistics, survival analysis, calibration, causal inference, bias / fairness metrics, study design
● MLOps: MLflow, Weights & Biases, DVC, Docker; experiment tracking and model registries
● Data platforms: PostgreSQL, BigQuery or Snowflake; Spark a plus
● Cloud & AI platforms: AWS SageMaker, GCP Vertex AI, or Azure ML
● Privacy & compliance: PHI / HIPAA handling, de-identification, and data governance (GDPR / PIPEDA aware)

Work arrangement
No