Role overview
- A Bachelor’s degree required (4-year degree).
- 3-6 years of full-time working experience in AI and/or Machine Learning
- Strong skills in Python
- Ability to collaborate and communicate effectively with diverse, hybrid and global teams
- Experience designing, building, and maintaining high-impact, high-value production AI/ML solutions on a major cloud platform
- Proficient in Generative AI models and frameworks (e.g., OpenAI, Dall-e, Langchain, Retrieval Augmented Generation (RAG)) and experienced with ML packages like scikit-learn and PyTorch
- Experience with natural language processing and deep learning
- Extensive experience in DevOps tools (GIT, Azure DevOps), Agile methodologies (Jira), and CI/CD pipelines for developing, deploying, and scaling analytical solutions
- Experience with MLOps and ML workflows, including data ingestion, transformation, and evaluation
- Experience with model retraining and feedback loop methodologies
- Experience with model and solution monitoring and reporting
- Understanding of data structures, data modelling, and software engineering best practices
- Strong foundation in mathematics, statistics, and operations research, with proficiency in data manipulation tools (SQL, Pandas, Spark) and deep learning techniques
- Familiarity with the types of data used across pharmaceutical commercial, clinical, and R&D functions, along with an understanding of the key standards that help these datasets work together
- Excellent communication skills for conveying findings and recommendations, with a willingness to travel for client engagements
What you'll work on
You will be joining a dynamic and interdisciplinary team of scientists and engineers who love to tackle the most challenging computational problems for our clients. We love to think creatively, build applications efficiently, and collaborate in both the ideation of solutions and the pursuit of new opportunities. Many on our team have advanced academic degrees or equivalent experience in industry.
You will spend your time on key responsibilities that include:
- Researching and implementing scalable AI systems that meet business requirements.
- Enhancing data pipelines and storage for optimal data accuracy and cleanliness.
- Monitoring and optimizing learning processes to improve high-performance models.
- Developing AI and data engineering solutions for life sciences by understanding sector‑specific datasets such as commercial, clinical, and R&D data, and aligning technical approaches to these needs.
- This position may have travel requirements as needed to engage with external clients regularly.
Skills and attributes for success
To excel in this role, you will need a blend of technical expertise and interpersonal skills. Your ability to navigate complex challenges and deliver impactful solutions will be essential.
This role will work to deliver tech at speed, innovate at scale and put humans at the center. Provide technical guidance and share knowledge with team members with diverse skills and backgrounds. Consistently deliver quality client services focusing on more complex, judgmental and/or specialized issues surrounding emerging technology. Demonstrate technical capabilities and professional knowledge. Learn about EY and its service lines and actively assess and present ways to apply knowledge and services.
- Hands-on experience implementing AI/ML pipelines that support drug discovery and development, covering data ingestion/curation, model training/validation, and deployment in compliant environments.
- Strong analytical and decision-making skills to guide project direction.
- Proven experience in project management and tracking deliverable completion.
- Ability to build and maintain relationships with clients and team members.
- Excellent communication skills to convey complex ideas effectively.