Data Science
Machine Learning (ML)
Deep LearningJob Description: Data Scientist – Data Engineering & Generative AI (Healthcare Data)
Location: Remote
Company: DocNexus.ai
About Us
DocNexus.ai is transforming how healthcare organizations leverage large-scale clinical and real-world data to accelerate innovation. We work with terabytes of structured and unstructured healthcare data, building secure, scalable platforms and advanced AI solutions that unlock insights for life sciences, payers, and providers.
Role Overview
We are seeking a Data Scientist with strong Data Engineering and Generative AI expertise to join our growing team. You will be responsible for designing, building, and scaling data pipelines and AI models that can process terabyte-scale healthcare datasets (clinical data, claims, EMRs, scientific publications, etc.) and power novel generative AI applications.
This role requires someone comfortable at the intersection of data engineering, machine learning, and applied research, who thrives in solving real-world problems in healthcare data.
Responsibilities
- Data Engineering & Architecture
- Design and maintain scalable data pipelines for terabyte-scale healthcare data (structured + unstructured).
- Build data ingestion, transformation, and storage workflows using modern cloud platforms (GCP/AWS/Azure).
- Ensure compliance with HIPAA, HITRUST, and data privacy standards.
- Machine Learning & Generative AI
- Develop and fine-tune LLMs, RAG pipelines, and multimodal AI models for healthcare-specific use cases.
- Apply ML/AI methods for clinical NLP, patient journey analytics, real-world evidence, and predictive modeling.
- Optimize model performance at scale, including distributed training and inference.
- Collaboration & Impact
- Partner with product managers, clinicians, and data engineers to translate healthcare problems into scalable AI solutions.
- Contribute to the development of DocNexus.ai’s AI-driven platform and customer-facing applications.
- Mentor junior team members in both data engineering and AI best practices.
Qualifications
- Education & Experience
- MS or PhD in Computer Science, Data Science, Engineering, or related field (or equivalent experience).
- 4+ years of experience working with large-scale data pipelines and advanced machine learning models.
- Technical Skills
- Expertise in Python, SQL, and distributed data frameworks (Spark, Beam, Dask, or similar).
- Experience with cloud platforms (GCP preferred, AWS/Azure okay) and large-scale data warehousing (BigQuery, Snowflake, Redshift).
- Strong background in LLMs, transformers, and generative AI frameworks (LangChain, Hugging Face, Vertex AI, OpenAI APIs).
- Experience with data orchestration tools (Airflow, Prefect, or Dagster).
- Proficiency with ETL pipelines, APIs, and streaming data frameworks (Kafka, Pub/Sub).
- Domain Knowledge
- Familiarity with healthcare data standards (HL7, FHIR, claims, EHR/EMR, clinical trials).
- Experience working with PHI/PII data governance and compliance.
- Soft Skills
- Strong problem-solving mindset and ability to work in ambiguous, high-scale environments.
- Excellent communication skills for cross-functional collaboration.
- Passion for using AI to make a real-world impact in healthcare.
Why Join DocNexus.ai
- Opportunity to work on cutting-edge healthcare AI with terabyte-scale datasets.
- Collaborative, mission-driven team accelerating innovation in healthcare.
- Competitive compensation, equity options, and comprehensive benefits.
- Flexible remote-first culture with opportunities for in-person collaboration.
Shubham Vishwakarma
Full Stack Developer - Averlon
About DocNexus Co
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