Analyst, Data Analytics

Position Title: Analyst, Data Analytics

Work Location: Irvine, CA (Hybrid)

Assignment Duration: 12 Months

Position Summary:

Perform quantitative analysis using Python (e.g., pandas, NumPy, visualization libraries) to support clinical trial operations such as enrollment, costing, and resourcing, and to develop forecasting and decision-support outputs for key stakeholders (e.g., Clinical Affairs, Regulatory and Medical Affairs, Strategy, Global Supply Chain, Finance).

Investigate, assess, and interpret clinical and operational data to support strategic decision-making, including early signal detection related to enrollment trends, protocol adherence, site performance, and data quality, while proposing moderately complex solutions and recommendations.

Key Responsibilities:

• Perform quantitative analysis using Python (e.g., pandas, NumPy, visualization libraries) to support clinical trial operations such as enrollment, costing, and resourcing, and to develop forecasting and decision-support outputs for key stakeholders (e.g., Clinical Affairs, Regulatory and Medical Affairs, Strategy, Global Supply Chain, Finance).

• Investigate, assess, and interpret clinical and operational data to support strategic decision-making, including early signal detection related to enrollment trends, protocol adherence, site performance, and data quality, while proposing moderately complex solutions and recommendations.

• Modify, extend, and maintain analysis tools and workflows—primarily in Python—by leveraging existing clinical models (e.g., inventory, case management, headcount, trial enrollment, site activations/deactivations) while applying clinical trial domain knowledge.

• Organize, analyze, and create reproducible analyses, reports, dashboards, and data extracts to summarize moderately complex challenges across clinical affairs projects, programs, and initiatives.

• Apply statistical methods (e.g., descriptive statistics, trend analysis, basic inferential methods) as appropriate to quantify uncertainty, monitor performance, and support interpretation of clinical and operational signals.

• Lead portions of clinical analytics projects in collaboration with cross-functional stakeholders (e.g., Clinical Operations, Biostatistics, vendors, and internal analytics partners).

• Identify and propose data-driven process improvements related to clinical affairs operations (e.g., screening efficiency, site start-up, physician training, data review workflows).

• Other duties as assigned.

Qualification & Experience:

• Bachelor's Degree Required

• 3 years of previous related experience Required

• Experience in a quantitative, analytical, or programming-heavy role Preferred

• Experience working in clinical research or clinical trial operations within the medical device industry Preferred

• Strong proficiency in Python for data analysis, including developing maintainable scripts and notebooks for clinical and operational datasets

• Proven expertise in Excel and PowerPoint and other MS Office Suite applications (Word, Access)

• Solid understanding of quantitative and statistical methodologies, with the ability to apply them pragmatically in a clinical operations context

• Experience with signal detection, trend monitoring, or anomaly identification in complex datasets preferred

• Good written and verbal communication skills and interpersonal relationship skills

• Strong problem-solving, organizational, analytical, and critical-thinking skills

• Moderate knowledge and understanding of client's policies, procedures, and guidelines relevant to clinical trial data analytics

• Strict attention to detail and data quality

• Ability to interact professionally with all organizational levels

• Ability to manage competing priorities in a fast-paced environment

• Ability to work collaboratively in team and cross-functional environments

• Ability to build productive internal and external working relationships

• Adhere to all company rules and requirements (e.g., Environmental Health & Safety policies) and take appropriate measures to protect people, data, and the environment.