CCI Consultant / Sr. Consultant, Clinical Trial Foundation

The Clinical Operations Analytics Consultant should be highly motivated and results-driven Analytics and AI Specialist to join our team. The candidate should have a strong background in data analytics, understanding and practical experience of artificial intelligence (AI), and machine learning, with the ability to apply advanced techniques to solve complex business problems. As part of our growing analytics and automation team, you will be responsible for leveraging data to uncover insights, optimize processes, and contribute to analytics and AI-based product and service development.

 

Responsibilities:

1. Systems Development and Management
Maintain and grow a strong working knowledge of the various systems used across CDDA in clinical trials.
Partner across functions and geographies to build and/or refine systems used in operational reporting and analytics.
Resolve system/product issues quickly to ensure continued access to needed operational information; apply root cause analysis as needed.
Ensure high stakeholder satisfaction through consistent delivery of high quality, timely and insightful outputs throughout analytics value chain.
Apply knowledge and understand and respond to customer feedback on reports and dashboards to continuously improve product functionality and efficiency.
Develop and support user training as needed, including maintenance of job aids, FAQs, knowledge articles, etc
Develop expertise of processes and data used by business functions.
Support system testing and develop validation documentation as needed.

2. AI and Analytics
Utilize statistical methods, data mining, and data visualization techniques to uncover trends, patterns, and correlations.
Develop and deploy dashboards, key performance indicators (KPIs) and automated tools across business functions to streamline processes and operations.
Design, develop, and implement AI and machine learning models to solve business challenges.
Build predictive models and recommend solutions based on statistical analysis and machine learning algorithms.
Collaborate with product and engineering teams to integrate AI models into business operations and software applications.
Follow appropriate business processes for integration of data and presentation of analytics.
Automate data pipelines, data cleaning, and transformation processes to improve efficiency.
Networks with appropriate IT colleagues to determine solutions to meet business partners needs.
Provide consultation, advice, and coaching to less senior team members as needed.

Research & Development:
Stay up to date with the latest advancements in AI, machine learning, and data analytics.
Contribute to research and development projects to develop innovative AI/Analytics automated solutions.

Basic Requirements:

• bachelors or masters degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
• Expertise with data analysis/visualization applications, languages, and analytics solutions, for example, Power BI, Tableau, Excel, Python, R, R Shiny, AWS, SQL etc
• Understanding of Microsoft Power Platforms (PowerApps, Power Automate etc) and Fabric.
• Knowledge of machine learning algorithms (eg, regression, classification, clustering, reinforcement learning).
• Proficiency in statistical analysis and hypothesis testing.
• Familiarity with big data technologies (eg, Hadoop, Spark) and/or cloud platforms (eg, AWS, Azure).
• Demonstrated ability to deliver clear and concise data interpretation and communications.
• Excellent communication skills, with the ability to explain complex AI concepts to non-technical stakeholders.
• Demonstrated ability to work with business owners to define key business requirements and convert to technical specifications
• Experience working with business intelligence tools and databases.

Additional Skills/Preferences:
Experience working with clinical data in a pharmaceutical, biotech, CRO, or Regulatory agency.
Familiarity with systems used in clinical trials like Planisware, Impact, Oracle, Veeva suite, etc
Familiarity with AI ethics and responsible AI practices.
Experience in automating business processes using AI technologies.
Demonstrated proactive process improvement.
Ability to work in an Agile environment and collaborate with cross-functional teams.
Relevant certifications in data science, AI, or machine learning (eg, AWS Certified Machine Learning, Google Cloud AI Engineer).