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.