Senior Manager, R&D AI/ML Engineer (Remote)

Brief Description:

The Senior Manager, R&D AI/ML Engineer in Information Services (IS) will play a critical role in driving the adoption and implementation of AI/ML-driven analytics solutions across global business functions with a primary focus on R&D. As a key member of a talented team of advanced data solutions experts, this role will leverage machine learning, deep learning, and generative AI to enhance data-driven decision-making and optimize business processes.

The Sr. Manager will collaborate closely with R&D stakeholders- and IS business partners to scope and design scalable, fit-for-purpose AI/ML models. Responsibilities will include developing, deploying, and operationalizing AI/ML solutions that enable harmonized, real-time insights for scientific and operational advancements. Additionally, this role requires knowledge global pharmaceutical industry regulations and practices, data engineering, and predictive analytics to address complex data challenges and drive innovation in alignment with our data strategy.

Essential Functions

As a Senior Manager, R&D AI/ML Engineering within Biopharma IS, this role will focus on the design, development, and implementation of AI/ML-driven solutions to support R&D and other related business functions, e.g. Commercial. The role will work independently as a subject matter expert (SME), collaborating with stakeholders and IS partners to deliver technical AI/ML solutions that generate actionable insights.

• Develop AI/ML models to support scientific and operational use cases across R&D functions, or other priorities in other Jazz areas e.g. Commercial

• Work closely with R&D teams and IS partners to identify appropriate machine learning, deep learning, and generative AI opportunities for specific business challenges

• Ensure AI/ML models are reliable, scalable, and compliant, following best practices in model development, validation, and monitoring. Consideration will be given to post-go live model operations and model maintenance including monitoring for drift

• Follow ML Ops best practices, including model retraining, CI/CD automation, and deployment pipelines for AI/ML solutions

• Analyze large-scale and diverse datasets, applying appropriate data preprocessing, feature engineering, and optimization techniques

• Work closely with R&D business stakeholders, IS business partners, and system owners to understand data needs and AI/ML opportunities

• Participate in cross-functional technical discussions, providing technical guidance on model selection, algorithm optimization, and best practices

• Collaborate with IS teams (such as Cloud Infrastructure, Information Security, Data Strategy and Data Operations) to ensure smooth integration and deployment of AI/ML models within existing infrastructure

• Document AI/ML processes, model performance, and lessons learned to support knowledge sharing and reproducibility

Required Knowledge, Skills, and Abilities

• Strong collaboration skills including communication, teamwork and the ability to prioritize and align advanced data solutions with the complex business problems

• Demonstrated excellent teamwork, collaboration and interpersonal skills, ability to take initiative, and meet challenges with a can-do attitude

• Ability to understand and support complex business problems and explain complex machine learning concepts to non-experts

• AI/ML understanding in supervised and unsupervised learning, such as SVM, Random Forest, clustering and regression models

• Understanding in deep neural network architectures, such as CNN, RNN, GRU, LSTM, etc

• Hands-on experience in Python data analytics & ML libraries such as sk-learn, Pandas, Keras, Tensorflow, Pytorch and etc

• Hands-on experience in Generative AI and Large Language Model (LLM) evaluation, implementation and fine-tuning

• Hands-on experience in natural language processing (NLP) development and implementation

• Demonstrated experience in retrieval augmented generation (RAG) and SQL analyzer architecture

• Knowledge of software systems and database principles

• Familiar with Cloud computing (e.g. AWS) and high-performance computing using GPU, e.g. CUDA

• ML Ops, such as model deployment and CI/CD experience preferred

• Demonstrated ability to work and manage on multiple projects at the same time

• Experience in biopharma and/or healthcare industry is a preference

• Working knowledge of data analytics and visualization tools (e.g. Power BI, Tableau) is a plus

• Working knowledge SQL, relational databases, and data modeling experience is a plus

• Excellent verbal and written communication skills

• Moderate travel (<10%) within the US may be required

Required/Preferred Education and Licenses

• 5-7 years of experience, bachelor's degree required and advanced degrees preferred e.g. Master's Degree, or PhD. in a Data Science, Applied Mathematics, Computer Science, Statistics, or other relevant fields