Senior Data Scientist, Clinical Analytics (On-Site, Il Based)

Job Description
Purpose:
A team of data scientists with a unique blend of Business, Scientific, and Machine Learning expertise who seek to:
Unleash the full potential of AbbVie’s data assets by bringing technology and/or data and insights to the forefront of decision making via fit-for-purpose data analytics solutions
Broaden the scope and impact of Analytics and Data Science by constantly exploring new opportunities to transform clinical development and R&
D
Collaborate with stakeholders to outline the problem, explore solutions, refine opportunities and deliver a product with a continuous innovation mindset
Responsibilities:
Connects with cross-functional teams to design work product and as an analytics consultant. Anticipates and identifies issues that could affect timelines or quality and develops options and solutions
Leads and helps establish the design principles and standards to ensure analytical work product is consistent across projects where appropriate and that user experience is optimized
In addition to standard statistical methods, develops prototypes, test methods and algorithms. Leverages emerging statistical methodologies, ML and AI to drive innovative analytical solutions to create insights
Enables data-driven insights to support of clinical development continuum, including precision medicine
Ensures adherence to federal regulations and applicable local regulations, Good Clinical Practices (GCPs), ICH Guidelines, AbbVie Standard Operating Procedures (SOPs), and to functional quality standards. Stays abreast of new and/or evolving local regulations, guidelines and policies related to clinical development
Identify business needs and support the creation of standard KPIs, reports, and statistical analyses;
Responsible for coaching and mentoring junior team members.
Work side by side with cross-functional teams as an analytics consultant to strategize on how analytics can help evaluate the progress of clinical trials, as well as facilitate discussions around emerging risks;
Applies machine learning techniques to validate assumptions and predict future behavior
Significant Work Activities -Continuous sitting for prolonged periods (more than 2 consecutive hours in an 8 hour day)