Senior Data Analyst, Clinical Evidence Strategy and Implementation

2 weeks ago

Miami, United States Omni Inclusive Full time

Description/Comment: o The Senior Data Analyst, Clinical Evidence Strategy and Implementation will have the opportunity to:
Analyze hundreds of thousands of heterogeneous medical records including lab results, medical history, instrument measurements, hospital procedures, etc.
Interpret complex real-world clinical data
Clearly communicate findings with statistics and data visualization to drive evidence-based decisions.
Evaluate data errors, trends, and collection issues; present findings/recommendations to clinical teams and management for resolution
Serve as a liaison between key stakeholders from Data Science, Medical and Scientific Affairs and Marketing teams to ensure data quality processes are implemented and followed.
Work with stakeholders to understand data requirements for Client projects and support with building the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, AWS, and Azure
Support data management for clinical studies, such as data management plan, eCRF design, non-product software validation and adjudication strategy.
Identify, design, document and implement continuous process improvements such as interpretation and strategy of clinical data issues.
Utilize clinical expertise to advise on specific targets for predictive models with endless possibilities to explore.
Be involved with the full cycle of problem definition, data acquisition, organization, and data exploration and outcome phenotyping for Clinical Decision Support (CDS) Solutions.

The essential requirements of the job include:
Bachelors degree (Master's preferred) in clinical data science, data analytics, statistics, life sciences or related fields with 5+ years of experience.
3+ years of experience with Electronic Medical Record data (Epic, Cerner, etc.)
Require experience with Python for data analysis and visualization.
Knowledge of statistical computing, machine learning and data visualization tools.
Experience with shared data science development and analytics environments.
Experienced with real-world clinical data management documentation to support regulatory submissions.
Ability to effectively summarize results from analysis to a diverse set of audiences with varying backgrounds and technical skills.
Excellent problem-solving and critical thinking skills
Ability to manage competing priorities in a fast-paced environment
Strict attention to detail
Must be able to work in a team environment, including cross-departmental teams and key contact representing the organization on projects
Ability to interact with senior internal and external personnel on significant matters often requiring coordination between organizations
Willingness to travel occasionally as needed (up to 10%) required

It would be a plus if you also possess previous experience in:
Experience in the fields of clinical informatics to improve health outcomes.
Understanding QMS processes for medical devices.
Previous work experience in a clinical setting (hospital preferred).
Knowledge of sepsis and host immune response disease states.

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