Data Scientist

Key Responsibilities:

1. Advanced Machine Learning & AI Engineering

• Design, develop, and optimize supervised, unsupervised, and reinforcement learning models.
• Implement and fine-tune deep learning architectures using frameworks such as TensorFlow and PyTorch.
• Apply ethical AI principles, including fairness, transparency, privacy, and bias mitigation.
• Deploy and monitor models in production environments, ensuring scalability and reliability.

2. Data Engineering & Cloud-Native Architecture

• Build and maintain scalable data pipelines and ETL processes for real-time and batch analytics.
• Engineer robust data architectures using Spark, MetaFlow, Databricks, and cloud platforms (Azure, AWS, GCP).
• Manage and manipulate large healthcare datasets for model development and analytics.
• Ensure data quality, integrity, and security throughout the analytics lifecycle.

3. Statistical Modeling & Quantitative Analysis

• Apply advanced statistical methods, hypothesis testing, and predictive analytics to healthcare data.
• Design and interpret causal AI experiments to support business and clinical decision-making.
• Develop and validate predictive models for patient outcomes and operational efficiency.

4. Data Visualization & Communication

• Create compelling visualizations using Tableau, Power BI, D3.js, or similar tools.
• Translate complex data and analytics into clear, actionable insights for technical and non-technical stakeholders.
• Communicate findings effectively to engineering, product, and clinical teams.

5. Healthcare Domain Expertise & Compliance

• Ensure solutions adhere to healthcare data standards (HL7, FHIR) and regulations (HIPAA, GDPR, CCPA).
• Work with clinical datasets and understand healthcare workflows to ensure relevance and compliance.
• Stay current with healthcare regulations and data privacy requirements.

6. Collaboration & Continuous Learning

• Work closely with product, engineering, clinical, and compliance teams to deliver integrated, data-driven solutions.
• Share knowledge and mentor team members on data science concepts and tools.
• Commit to continuous improvement and staying current with industry trends and best practices.

Required Qualifications:

Education & Experience Guidelines

• Bachelor's degree in computer science, data science, or other relevant field. 
• 5-8 years of relevant work experience
• Experience developing predictive models and working with healthcare data standards.
• Occasional travel may be required. 

Other Preferred Knowledge, Skills, Abilities or Certifications:

• Cloud Platforms: AWS, Azure, GCP
• AI Tools: Spark, MetaFlow, Databricks
• Healthcare Compliance: HIPAA, GDPR, CCPA
• Healthcare Standards: HL7, FHIR
• AI Ethics: Fairness, transparency, bias mitigation
• Certifications: Azure Data Scientist Associate, Google Cloud Data Engineer, CHDA, IBM Data Science
• Visualization Tools: Tableau, Power BI, d3.js
  • Communication: Ability to translate complex data into actionable insights