Clinical Data Analyst

Title: Clinical Data Analyst

Duration: 12 Months

Location: Remote

Only W2 candidates are eligible for this position. Third-party or C2C candidates will not be considered.

Description:

Responsibilities

• Develops study specific annotated CRFs, database documentation, edit check specifications, data handling conventions and data entry instructions.
• Programs SAS edit checks and SAS macros for clinical trials, encompassing ETL processes, data validations, statistical analyses, and report generation.
• Design and develop robust ETL/ELT pipelines for structured and unstructured data.
• Hands-on database administrator skills to manage or identify root cause and resolve issues stemming from the management of structured and/or unstructured data sources.
• Conduct data automation tasks, including software development, testing, and validation. Familiarity with Power BI, R, Python, HTML, JavaScript, and REST APIs for data downloading is a plus.
• Collaborate with biostatistics, data scientists, analysts, and stakeholders to support AI/ML model development and deployment.
• Build and optimize data systems for performance, scalability, and reliability.
• And ensure data quality, integrity, and security across platforms.
• Knowledge of the software development life cycle (SDLC) and experience in coding and design. Develop and maintain documentation for data architecture, processes, and workflows.
• Experienced in Rest API connection.

Required Skills

• Experience with clinical data management documentation, CRF development, EDC building, data quality check
• Experience with data automation tools and the building and optimizing robust ETL/ELT pipelines for structured and unstructured data
• Programs SAS edit checks and SAS macros for clinical trials

Preferred Skills

• Data visualization software such as Power BI, Python, RShiny
• Advanced SQL knowledge and experience with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
• Exposure to AI/ML concepts and experience supporting model pipelines

Software Skills

• SAS include SAS base/Macros/graph/listing
• Data visualization software such as Power BI, Python, RShiny
• Data pipeline and workflow management tools Web Rest API connection
• Advanced SQL knowledge and experience with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases;
• Exposure to AI/ML concepts and experience supporting model pipelines
• A working knowledge of manipulating, processing, and extracting value from large datasets.

Education

• Minimum of a Bachelors’ Degree required; Advanced Degree preferred. Desired fields of study include Computer Science, Data Science, Statistics, Informatics, Information Systems or related quantitative field.