Sr Data Scientis

Technical Skills

·     Data Management and Integration

o  Proficiency in collecting, cleaning, and preprocessing clinical data from diverse sources, including health insurance claims and electronic health records (EHRs).

o  Experience with integrating and managing large-scale datasets from sources like CPRD and claims databases.

·     Statistical and Machine Learning Techniques

o  Knowledgeable in Federated Machine Learning Techniques

o  Advanced knowledge of statistical methods and machine learning algorithms for data analysis and predictive modeling.

o  Experience with techniques such as regression, classification, clustering, and ensemble methods to build and validate predictive models.

·     Programming and Data Analysis

o  Strong programming skills in languages such as Python or R for data manipulation, analysis, and model development.

o  Strong SQL knowledge and experience

o  Familiarity with data analysis libraries and frameworks (e.g., pandas, scikit-learn, TensorFlow).

·     Medical Coding Systems

o  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

o  Ability to create clear and informative visualizations using tools like Tableau, Matplotlib, or Seaborn.

o  Skilled in preparing detailed reports and presentations that communicate complex findings to both technical and non-technical stakeholders.