Sr. Data Science Engineer (Remote)

Job Description
Come to work each day with an inclusive and collaborative business technology team. As a Senior Data Science and Analytics Engineer in AbbVie Business Technology Solutions (BTS), you’ll have opportunities to contribute to the digital transformation of a leading biopharma company, helping to create solutions that impact patients and their communities for the better.
In this role, you’ll be responsible for:
Advanced analytics knowledge of best-in-class data science methodologies, deep understanding of AI/ML space, proven track record of solving business problems using data science and ability to work with business and cross functional teams to deliver and execute complex analytics problems.
Develop curated datasets using Dataiku or similar tools like Alteryx per business use cases and facilitate self-service analytics.
Self-starter, comfortable with ambiguity, experience initiating and driving projects with minimal oversight and guidance.
Exceptional analytical skills on complex datasets and experience solving ambiguous problems using data with interest to establish robust measurement frameworks.
Proven track record of leveraging data to deliver business value and present data-driven insights to senior leaders.
Explore and extract data from multiple sources and analyze it to discover trends and patterns, create meaningful insights and apply strong knowledge of data science for making informed decisions based on data insights.
Design/Develop data visualizations to effectively communicate data findings to both technical and non-technical audiences.
Develop processes and tools to monitor and analyze model performance and data accuracy and lead the advanced analytics framework through AI/ML.
Establish and follow data science best practices including peer review, code review, documentation, coding standards, data quality and ensure reproducibility and compliance.
Serve as internal SME on Dataiku platform and drive the self-service COE with office hours training and establish data governance around the curated datasets and metrics, and best practices on taxonomy, and other.