Sr Data Scientist at InfoVision

Job Title: Sr. Data Scientist

Duration: Long-term

 

Technical Skills:

Data Management and Integration

• Proficiency in collecting, cleaning, and preprocessing clinical data from diverse sources, including health insurance claims and electronic health records (EHRs).
• Experience with integrating and managing large-scale datasets from sources like CPRD and claims databases.

Statistical and Machine Learning Techniques

• Knowledgeable in Federated Machine Learning Techniques
• Advanced knowledge of statistical methods and machine learning algorithms for data analysis and predictive modeling.
• Experience with techniques such as regression, classification, clustering, and ensemble methods to build and validate predictive models.

Programming and Data Analysis

• Strong programming skills in languages such as Python or R for data manipulation, analysis, and model development.
• Strong SQL knowledge and experience
• Familiarity with data analysis libraries and frameworks (e.g., pandas, scikit-learn, TensorFlow).

Medical Coding Systems

• Expertise in using medical coding systems, including ICD-9, ICD-10, and SNOMED CT, for mapping clinical data and integrating with predictive models.

Data Visualization and Reporting

• Ability to create clear and informative visualizations using tools like Tableau, Matplotlib, or Seaborn.
• Skilled in preparing detailed reports and presentations that communicate complex findings to both technical and non-technical stakeholders.

 

Domain Knowledge:

Clinical Data

• Understanding of clinical datasets, including the types of data collected (e.g., laboratory results, diagnoses, treatments) and how they relate to Type 1 Diabetes.
• Experience with longitudinal and cross-sectional clinical data, including knowledge of health outcomes and patient demographics.

Healthcare Regulations

• Knowledge of regulatory requirements related to clinical data, including data privacy laws such as HIPAA and GDPR.
• Familiarity with ethical considerations and data security protocols in handling sensitive health information.

 

Collaborative Skills:

Cross-Functional Collaboration

• Ability to work effectively with healthcare professionals, researchers, and data engineers to align project goals and validate data and model outcomes.
• Experience in collaborating with interdisciplinary teams to ensure the integration of clinical insights into data science workflows.

Communication Skills

• Strong verbal and written communication skills to present technical findings and recommendations to various stakeholders, including non-technical audiences.

 

Project Management:

Organizational Skills

• Capable of managing multiple tasks and priorities in a fast-paced environment, ensuring timely delivery of project milestones.
• Experience in documenting data processing workflows, model development procedures, and maintaining comprehensive records of analyses.

 

Additional Skills:

• Innovation and Problem-Solving
• Ability to innovate and troubleshoot data-related issues, including handling complex data integration and analysis challenges.
• Proactive approach to identifying opportunities for improvement in data processes and predictive modeling techniques