BIS AI / ML Data Engineer - ONC

About the Role

Key Responsibilities

• Design, develop, and deploy data engineering and machine learning models to address complex problems within the Oncology business unit.
• Build, train, and fine-tune models to achieve process and decision automation while ensuring scalability, efficiency, and accuracy.
• Perform data acquisition, cleaning, preprocessing, and feature engineering to optimize model performance.
• Integrate models or workflows into existing Incyte business systems.
• Stay updated on advancements in artificial intelligence and machine learning, experimenting with new algorithms, frameworks, and tools.
• Collaborate with cross-functional teams and stakeholders, including Oncology, Dermatology, IT, and Compliance, to deliver AI/ML solutions.
• Develop, implement, and maintain data pipelines using Azure Data Factory, connecting with data sources like blob storage and SQL databases.
• Use Databricks for analyzing, processing, and transforming large datasets.
• Work with large language models (LLMs) like ChatGPT to develop conversational AI features via API programming.
• Design and implement data models and work with graph databases for predictive analytics.
• Create interactive dashboards and applications with R Shiny or other visualization tools.
• Develop and maintain APIs for data communication between systems.
• Manage project timelines, deliverables, and documentation independently, ensuring alignment with business and regulatory standards.

Requirements

• BS in Computer Science, Information Systems, Engineering, or a related field; advanced degree or certifications preferred.
• 3-5 years of hands-on experience building AI/ML solutions in industry or academia.
• Proficiency in Python for data processing, machine learning, and API integration.
• Experience with R and R Shiny for creating interactive visualizations and applications.
• Experience with Azure Cloud Platform and Azure Data Factory for data pipelines and storage systems.
• Strong knowledge of Databricks for data engineering and distributed model training.
• Familiarity with large language models (LLMs) like ChatGPT for conversational AI and NLP applications.
• Proven experience with SQL databases, including Azure Synapse, for querying, data integration, and reporting.
• Knowledge of graph databases and data modeling for predictive analytics.
• API programming skills for system integration.
• Understanding of predictive modeling techniques and machine learning algorithms.
• Strong communication skills to translate technical insights for non-technical stakeholders.
• Project management skills to handle multiple projects independently.

Nice to Have

• Experience with data security and governance tools such as Purview.
• Knowledge of data modeling techniques for structuring data to support analytics.

Qualifications

• Educational background in Computer Science, Information Systems, Engineering, or related fields.
• 3-5 years of relevant industry or academic experience in AI/ML development.

Benefits & Perks

• Not explicitly specified in the description.