About this role
Accenture seeks a consultant for AI and data science projects in healthcare and life sciences. The posting lists the role as S&C Global Network - AI - Life Sciences -Data Science Consultant; its detailed job description also calls it an AI - Healthcare Analytics - Consultant role. It is a full-time, Team Lead/Consultant-level position with a stated location of Bangalore/Gurgaon and an overall experience range of 5–10 years.
Responsibilities
- Advise global clients using data-driven recommendations; manage client communications, explain project progress, and present findings to stakeholders.
- Design and implement generative AI, retrieval-augmented generation (RAG), agentic AI, and traditional AI/ML solutions for healthcare and life sciences business challenges.
- Deliver consulting projects individually or in small to medium-sized teams, contributing to strategy, implementation, process design, change management, data engineering, data science, and business intelligence.
- Apply life sciences domain knowledge and design thinking to develop analytics solutions, improve business processes, assess implementation readiness, and support transformational change.
- Develop team assets, methodologies, research, or white papers; contribute to proposals and business development.
Required qualifications and experience:
- Bachelor’s or master’s degree in Statistics, Data Science, Applied Mathematics, Business Analytics, Computer Science, Information Systems, or another quantitative field.
- At least 4 years of successful project experience in life sciences, pharmaceuticals, or healthcare, plus experience creating and deploying generative AI and agentic AI solutions.
- Knowledge of pharmaceutical commercial, clinical, real-world evidence (RWE), and electronic medical record (EMR) data; hands-on experience with datasets such as Komodo, RAVE, IQVIA, Truven, or Optum.
- Experience building and deploying statistical and machine learning models, including segmentation, predictive modeling, hypothesis testing, multivariate analysis, time series techniques, and optimization. Proficiency in Python, SQL, working with large datasets, and using AWS, Azure, or Google Cloud to deploy and scale language models.
- Strong analytical, problem-solving, writing, communication, and presentation skills; ability to work with stakeholders and solve complex business problems.
Preferred skills include R, Spark, Databricks, data visualization tools such as Power BI, Tableau, QlikView, or Spotfire, and design thinking, business process optimization, and stakeholder management. The posting notes opportunities to work with global pharmaceutical clients and access personalized training.