Data Scientist Recommender Systems (Healthcare)

Location: Remote

Job Type: Contract

Experience: 3-8 years

Industry: Healthcare, HealthTech, Digital Health, Pharma

About The Role

We are looking for a Data Scientist specializing in Recommender Systems to develop personalized healthcare recommendation models that improve patient outcomes, enhance clinical decision-making, and optimize user engagement on digital health platforms. You will work on AI-driven recommendation engines for medication adherence, treatment pathways, clinical decision support, and personalized wellness programs.

Key Responsibilities

Design and develop AI-powered recommendation systems to personalize treatment plans, drug recommendations, preventive care, and wellness suggestions.
Implement collaborative filtering, content-based filtering, and hybrid recommendation models to provide tailored healthcare recommendations for patients, doctors, and care providers.
Apply Natural Language Processing (NLP) and embeddings (BERT, BioBERT, Med-BERT) to extract insights from clinical notes, medical literature, and EHRs (Electronic Health Records).
Work with graph-based recommendations (Knowledge Graphs, Graph Neural Networks) to enhance precision in disease diagnosis, drug interactions, and treatment suggestions.
Develop personalized patient engagement models using predictive analytics and AI to improve adherence to medications and health regimens.
Optimize recommendation systems using evaluation metrics such as NDCG, MRR, MAP, Precision@K, and Recall@K.
Collaborate with healthcare providers and clinical experts to validate and interpret model outputs for patient-centric decision-making.
Ensure compliance with HIPAA, GDPR, and other healthcare data privacy regulations while handling sensitive patient information.
Deploy scalable recommendation models using AWS/GCP/Azure, MLflow, TensorFlow Serving, Docker, and Kubernetes.
Research and apply state-of-the-art healthcare AI techniques, including Federated Learning for privacy-preserving recommendations.

Required Skills & Qualifications:

3+ years of experience in Machine Learning, Deep Learning, and Recommender Systems in a healthcare or digital health setting.
Strong programming skills in Python, SQL, and ML frameworks such as TensorFlow, PyTorch, Scikit-learn.
Experience working with medical datasets such as EHRs, claims data, clinical trial data, and genomic data.
Solid knowledge of collaborative filtering (ALS, SVD, NMF), content-based filtering, and hybrid models.
Understanding of healthcare ontologies (SNOMED-CT, ICD-10, RxNorm, UMLS) for structured recommendation models.
Proficiency in Big Data technologies such as Apache Spark, Hadoop, and Kafka for large-scale patient data processing.
Hands-on experience with ML model deployment (Docker, Kubernetes, MLflow, Airflow).
Strong understanding of evaluation techniques for recommendation models, including real-world testing and A/B testing in healthcare settings.

Preferred Qualifications

Master's or PhD in Computer Science, AI, Machine Learning, Bioinformatics, or a related field.
Experience in digital therapeutics, personalized medicine, or AI-driven clinical decision support systems.
Familiarity with Federated Learning to ensure patient data privacy and compliance with HIPAA & GDPR.
Experience working in HealthTech, Pharma, Hospitals, or Medical AI startups.
Knowledge of FHIR, HL7, and other healthcare interoperability standards for integrating AI recommendations into clinical workflows.

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Data Scientist – Recommender Systems (Healthcare)