Come to work each day with an inclusive and collaborative business technology team. As a Data Scientist in AbbVie Business Technology Solutions (BTS), you will 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.

Responsibilities:

• A successful candidate will bring advanced analytics knowledge of best-in-class data science methodologies, deep understanding of AI/ML space, proven history of solving business problems using data science and ability to work with cross-functional teams to deliver and execute complex analytics problems.
• Experience with Natural Language Processing (NLP) techniques, LLM prompt engineering, LLM-based solution architecture such as retrieval-augmented generation and AI Agent development.
• Develop processes and tools to monitor and analyze model performance and data accuracy and lead the advanced analytics framework through AI/ML.
• Experience in working with complex data sets (unstructured and structured data) to solve business use cases by establishing robust measurement frameworks and deliver business value with data-driven insights to senior leaders.
• Experience in data discovery and analysis to discover trends and patterns, meaningful insights and apply strong knowledge of data science for making informed decisions.
• Design/Develop data visualizations to effectively communicate insights to both technical and non-technical audiences.
• Establish and follow data science’s best practices including peer review, code review, documentation, coding standards, data quality and ensure reproducibility and compliance.
• Serve as internal Data Science SME and on advanced analytics platform like Dataiku and drive the self-service citizen data science COE with office hours training and establish data governance around the curated datasets and metrics, and best practices on taxonomy.
• Self-starter, comfortable with ambiguity, experience initiating and driving projects with minimal oversight and guidance.

Tools and skills you will use in this role:

• Data Prep and Data science platforms like Dataiku or similar tools
• Data Visualization Tools like Power BI, Tableau and ThoughtSpot
• Advanced SQL, Python, Spark, and a broad array of ML frameworks
• Cloud data warehouse Snowflake (Snow pipe, Stored Procs, Snowpark, Dynamic Tables, CTE)
• JIRA, CI/CD and Agile project methodology
• Predictive and prescriptive models, other statistical models, and knowledge in data science in general
• Cloud environment (AWS, Snowflake, Azure) with large datasets and with streaming data architectures.
• Demonstrated knowledge of large language models and generative AI.
• ML frameworks (Scikit-Learn, NumPy, SciPy, Pandas, XGBoost, Tensorflow, PyTorch, MXNet, LLM)