Generative AI - Data Scientists

About Lilly

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our 39,000 employees work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the globe.

About the Role

This position is for an expert in machine learning to help us extract value from our data. You will lead all the processes from data collection, cleaning, and preprocessing, to training models and deploying them to production. The key responsibilities will be to prepare modern Natural Language Technology (NLT) platforms to gain insights from key business data. The employee will be responsible for designing, implementing and managing data preparation and advanced analytics tools in addition to demonstrating insights from the varied sources of data to business users. Responsibilities also include developing and designing language understanding/generation systems and effectively using text representation techniques.

Our Advanced Analytical and Data Sciences organization is growing to support the entire Lilly enterprise, from Discovery to Development to Manufacturing and Commercialization of our medicines. We are playing a leading role in transforming the way the company discovers and develops new treatments, identifies personalized treatment regimens, drives efficiency in our operations and optimizes our commercialization of new products. We are doing this with an emphasis in the areas of machine learning and artificial intelligence, natural language processing and other approaches to unstructured data, advanced mathematical and predictive modeling, visual analytics and more.

Objectives of the Role

• Work in tandem with our engineering partners to identify and implement the most optimal cloud-based ML solutions for the company.
• Research, design and adopt cutting-edge NLG algorithms to address real-world challenges such as summarisation.
• Define and document best practices and strategies regarding deployment and infrastructure maintenance.
• Ensure ML Model performance, uptime, and scale, maintaining high standards of code quality and thoughtful design.
• Maintain a platform that automates creating, training, deploying and updating machine learning models.
• Managing BI Platforms in accordance with company security guidelines.
• Build effective relationships with business areas, strategic vendors, and key delivery partners such as the Advanced Analytics and Data Sciences (AADS) group to share expertise and seek opportunities to reuse internal processes and services, so we can streamline implementation and support of key systems.

Key Responsibilities Include

• Perform cutting edge research in natural language processing (NLP) technologies.
• Collaborate with analytics team members to design, implement and develop enterprise-level NLP capabilities, including data engineering, technology platforms, and algorithms.
• Evaluate and benchmark the performance of different NLP systems, and provide guidance on metrics and best practices.
• Apply NLP technologies to answer business questions, solve business challenges, and make real-world impact.
• Stay current with new technology trends in NLP.

Required Experience

Proven experience with the following:

• Designing, developing, and researching Machine Learning systems, models, and schemes through data science and data analytics prototypes.
• Understanding of Natural Language Processing (NLP), Natural Language Understanding (NLU) and Natural Language Generation (NLG).
• Develop and implement technical efforts to design, build, and deploy AWS ML models at the direction of lead architects, including large-scale data processing, computationally intensive statistical modeling, and advanced analytics.
• Familiarity with deep learning, machine learning and NLP/NLG frameworks (like Keras, TensorFlow or PyTorch etc.), HuggingFace Transformers and libraries (like scikit-learn, spacy, gensim, CoreNLP etc.).
• Should have experience in AWS services such as SageMaker, Elasticsearch, and general knowledge of AWS architecture & other services.
• Ability to write robust code in Python, Java and R.
• Experience optimizing model hyperparameter tuning for speed and cost.
• Experience in building MLOps pipeline using MLOps frameworks like Kubeflow, MLFlow, and DataRobot.
• Experience with Docker and Kubernetes.
• Familiarity with Eventbridge and AWS step function for workload orchestration.
• Experience with Agile Development.

Basic Qualifications

• Ph.D. in Computer Science, Statistics, Computer Engineering, Electrical Engineering, Information Science, Information Engineering or related field.
• 5+ years of experience in NLP.
• Deep understanding of NLP techniques and systems.