Sr Data Scientist at InfoVision
Dallas, TX 75342
About the Job
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