Senior Principal Applied Scientist - Health Sciences

Job DescriptionOracle Life Sciences is focused on delivering software solutions to help the world’s largest pharmaceutical companies positively impact people’s lives by supporting the cost-effective development of treatments for today’s most challenging health related issues.We are looking for hands-on Applied Scientists with expertise and passion in solving difficult problems in life sciences. We intend to revolutionize the life sciences industry by leveraging AI/ML and Generative AI and redefine customer experience.This is a greenfield opportunity to design and build new AI native cloud applications from the ground up. We are growing fast, still at an early stage, and working on new initiatives. You will be part of a team of hard-working, motivated, a diverse set of people, and given the autonomy as well as support to do your best work. It is a dynamic and flexible workplace where you’ll belong and be encouraged. We operate with a startup mindset. We’re working on big goals, and we need talented folks with equally big ambitions. Join us!About the JobWe're seeking a highly skilled Senior Principal Applied Scientist to modernize Oracle Life Sciences Safety One portfolio with AI native applications. As a Senior Principal Applied Scientist specializing in AI/ML, you will play a pivotal role in architecting, developing, and deploying state-of-the-art models to power our SafetyOne product suite. You will collaborate closely with cross-functional teams including product managers, software engineers, and data scientists to unlock machine learning capabilities in all our products. Our new platform will be built directly on Oracle Cloud Infrastructure (OCI) based on cloud native principles. We build to scale globally, leveraging state-of-the-art tooling, with zero downtime.Responsibilities

Work with Engineering team for training data acquisition and data analysis

Define and follow the process for ML use case evaluation and planning

Design, develop, and optimize RAG (Retrieval-Augmented Generation) models to facilitate effective information retrieval and integration of structured data, ontologies, knowledge graphs, or other forms of structured knowledge representation

Utilize vector databases and advanced indexing techniques to efficiently store and retrieve relevant information for conversational contexts

Explore, Fine-tune and optimize large language models such as Cohere for specific use cases in the Life sciences.

Evaluate model performance, interpret results, experiment with various training strategies and domain-specific fine-tuning to improve accuracy and efficiency.

Implement and experiment with cutting-edge NLP, NLU, and NLG techniques to solve various use cases.

Collaborate with engineers to integrate machine learning models into production systems, ensuring scalability, reliability, and performance

Interacts with product and service teams to identify questions and issues for data analysis and experiments.

Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources.

Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers.

ResponsibilitiesQualification

Master's degree or PhD in Computer Science, Engineering, Mathematics, or related experience

10+ years of experience in data science

Strong programming skills in Python, SQL and proficiency with machine learning libraries such as TensorFlow, PyTorch, or R.

Experience with cloud platforms (e.g., AWS, OCI) and containerization technologies (e.g., Docker, Kubernetes).

Solid understanding of NLP fundamentals and experience with NLU/NLG techniques such as sentiment analysis, entity recognition, and text generation.

Preference for expertise in developing RAG models, working with vector databases, and fine-tuning large language models.

Experience in life sciences and healthcare domain and experience in a complex global organization is a plus

Excellent problem-solving abilities and a pragmatic approach to building scalable and robust machine learning systems.

Strong communication skills with the ability to collaborate effectively with cross-functional teams and articulate complex technical concepts to non-technical stakeholders

You are comfortable with ambiguity. You have a strong sense of ownership, can define your own workplan, set goals for others, and can drive projects to completion

You are excited to learn new technologies and stay on the cutting edge of what’s possible

You’ve taken a product or platform from 0 to 1, you know what it takes to launch something

Minimum Qualifications: PhD Computer Science, Mathematics, Statistics, Physics, Linguistics or a related field with a dissertation, thesis or final project centered in Machine Learning Techniques OR Masters or Bachelor's in one or more of these fields. Minimum 6 years work experience in the areas of machine learning, computer vision, natural language processing or data mining with a PhD OR 10+ years experience with a Master’s or Bachelor's. Preferred Qualifications: Scientific thinking and the ability to invent, with a track record of thought leadership and contributions to the advancement of the field. Demonstrated experience in successfully designing and shipping models using machine learning, deep learning, and statistical modeling across different data domains and modalities. Experience shipping machine learning or statistical models. Demonstrated experience successfully delivering large-scale ML solutions for complex customer/business problems. Deeper technical understanding and broadened knowledge related to architecture. Broad expertise or unique knowledge; uses skills to contribute to development of company objectives and principles and to achieve goals in creative and effective ways. Training machine learning models with large scale data using techniques such as data and model parallels. Strong publication record, including at least one as lead author, in top-tier ML and NLP journals and/or conferences. Depending on the job there may be additional minimum requirements and/or preferred qualifications.About UsAs a world leader in cloud solutions, Oracle uses tomorrow’s technology to tackle today’s problems. True innovation starts with diverse perspectives and various abilities and backgrounds.When everyone’s voice is heard, we’re inspired to go beyond what’s been done before. It’s why we’re committed to expanding our inclusive workforce that promotes diverse insights and perspectives.We’ve partnered with industry-leaders in almost every sector—and continue to thrive after 40+ years of change by operating with integrity.Oracle careers open the door to global opportunities where work-life balance flourishes. We offer a highly competitive suite of employee benefits designed on the principles of parity and consistency. We put our people first with flexible medical, life insurance and retirement options. We also encourage employees to give back to their communities through our volunteer programs.We’re committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by calling +1 888 404 2494, option one.Disclaimer:Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law. Which includes being a United States Affirmative Action Employer