Clinical Business Integrator

Key Responsibilities:
Partner with clinical business stakeholders to discuss opportunities to optimize and transform using tech solutions.
Act as domain lead and represent the clinical tech team in discussions with clinical business teams.
Be an advocate of the data science vision of the tech team to introduce breakthrough innovations and cater to efficiency gains.
Work with Engineering team to design, develop, and maintain IT systems and applications used in clinical research and drug development.
Collaborate with clinical researchers, site personnel, data managers, and IT teams to implement and support clinical trial management systems (CTMS), electronic data capture (EDC) systems, and other relevant technologies.
Ensure compliance with regulatory requirements and standards (e.g., FDA, EMA, GxP, GDPR).
Develop IT solutions to digitize the clinical trial journey from protocol development to Clinical Study Report.
Provide technical support and troubleshooting for clinical applications.
Analyse and optimize workflows to enhance efficiency and data integrity in clinical trials.
Manage data integration and interoperability between different clinical and IT systems.
Stay updated with emerging trends and technologies in the clinical and IT fields.

Skills and Qualifications:
Proven experience (9+ years) in IT roles within clinical research and drug development environments.
Strong understanding of clinical trial phases (Preclinical, Phase I-IV) and associated regulatory requirements.
Experience working with research/clinical datasets (including large datasets) and performing data pre-processing & feature engineering (basic level)
Proficiency in clinical trial management systems (CTMS), electronic data capture (EDC) systems, and other relevant technologies.
Excellent problem-solving and analytical skills.
Strong communication and collaboration abilities.
Experience with data standards such as CDISC, SDTM, and ADaM.
Experience working with teams using programming languages such as Python, Java, C#, SQL or JavaScript.
Preferred exposure to AI/ML use cases in the clinical space
Familiarity with cloud computing and data security principles.

Preferred Qualifications:
Advanced degree in a related field.
Certifications in clinical research (e.g., CCRA, CCRP).
Experience with machine learning and artificial intelligence in clinical research.