Clinical Data Analyst

LOCATION SUMMARY:

This will be a hybrid role working out of our Austin, TX location

POSITION SUMMARY: 

We are seeking a dynamic Clinical Data Analyst to join our team and play a crucial role in advancing our clinical research efforts. This position offers an exciting opportunity to blend data expertise with healthcare knowledge to drive positive changes in patient care and medical research.

As a Clinical Data Analyst, you will play a critical role in the healthcare field by collecting, analyzing, interpreting, and de-identifying clinical data to support evidence-based decision-making and improve patient outcomes. You will work closely with healthcare professionals, researchers, and data management teams to ensure the accuracy, integrity, and accessibility of clinical data. Your insights and reports will contribute to advancements in medical research, treatment strategies, and healthcare quality improvement.

PRIMARY RESPONSIBILITIES: 

Data Collection and Validation:

• Gather and verify clinical and assay execution data from various structured and unstructured sources, such as LIMS systems, csv files, external SAS datasets, JSON and PDF files etc.
• Ensure data accuracy, consistency, and compliance with relevant standards and regulations (e.g., HIPAA).

Data Analysis and Interpretation:

• Employ statistical and data analysis tools to extract meaningful insights from clinical and pipeline analysis data.
• Assist in identifying trends, patterns, and anomalies that may impact patient care or research outcomes.
• Collaborate with researchers and bioinformaticians to define requirements for sample and data selection for research and study designs.

Reporting and Visualization:

• Create clear and concise reports, dashboards, and visualizations to communicate findings to both technical and non-technical stakeholders.
• Provide data-driven insights for improving clinical processes, patient care, and research protocols and to support decision-making.

Data Management:

• Maintain data repositories, databases, and data dictionaries for efficient data storage and retrieval.
• Monitor data quality and implement data cleaning procedures as needed.

Quality Assurance:

• Implement quality control procedures to ensure the accuracy, reliability, and secure delivery of clinical data.
• Monitor data analysis processes and identify areas for improvement.

Regulatory Compliance:

• Stay current with relevant regulations and standards in clinical research and data analysis.
• Ensure compliance with data privacy and security regulations (e.g., HIPAA, GDPR).

Collaborative Teamwork:

• Collaborate with multiple teams, including researchers, medical directors, bioinformaticians, biostatisticians & data scientists and IT professionals, to address data-related challenges and deliver clean and accurate data.
• Act as a liaison between data management and healthcare teams to bridge communication gaps.

Continuous Learning and Innovation:

• Stay abreast of emerging trends and technologies in clinical data analysis and healthcare.
• Identify opportunities for process improvements and innovation in data analysis methodologies.

QUALIFICATIONS: 

• Bachelor's degree in a related field (e.g., Statistics, Data Science, Computer Science, Healthcare Informatics etc). 
• Minimum of 2 years of experience in clinical data analysis or a related role preferably in a healthcare or pharmaceutical setting.
• Basic knowledge of clinical research methodologies and regulatory requirements, such as HIPAA and FDA guidelines.
• Experience with healthcare data, electronic health records (EHR), and clinical terminology is a plus.
• Basic understanding of next-gen sequencing workflows.
• Certification in data analysis or healthcare informatics is a plus.

KNOWLEDGE, SKILLS, AND ABILITIES:

• Proficiency in data analysis tools and programming languages (e.g., SQL, Python, R).
• Experience with healthcare data visualization tools  (e.g., Tableau, Power BI, Quick Sight).
• Basic understanding of machine learning and predictive modeling for healthcare applications.
• Strong SQL skills for querying and retrieving data from complex data sources in a structured format.
• Proficient in aggregating data, preparing, cleaning data and data mining using SQL and Python.
• Knowledge of healthcare terminologies and standards (e