AI - Healthcare Analytics - Consultant

Your job

• You will develop, deploy, and monitor AI/ML models in production environments and enterprise systems, including predictive analytics, anomaly detection, and process optimization solutions for clients.
• You will work with Generative AI models such as GPT, Stable Diffusion, and DALL·E to develop applications for content generation, automated documentation, code synthesis, and intelligent assistants.
• You will implement Agentic AI systems, including AI-powered automation, self-learning agents, and decision-support systems for industrial applications.
• You will design and build Autonomous AI solutions for use cases such as predictive maintenance, supply chain optimization, and Robotic Process Automation (RPA).
• You will work with structured and unstructured data from diverse sources, including IoT sensors, manufacturing logs, customer interactions, and other enterprise data sources.
• You will optimize and fine-tune Large Language Models (LLMs) for specific business applications while ensuring responsible, ethical, and explainable AI practices.

Capabilities

• You must have extensive GenAI expertise, with a proven track record of creating and deploying GenAI and Agentic AI solutions.
• You must have 4+ years of experience working on Life Sciences, Pharma, or Healthcare projects, with a demonstrated track record of delivering successful outcomes.
• You should have an excellent understanding of Pharma datasets, including Commercial, Clinical, RWE (Real-World Evidence), and EMR (Electronic Medical Records) data.
• You should have hands-on experience working across one or more areas, such as Real-World Evidence data, R&D Clinical data, or Digital Marketing data.
• You must have hands-on experience working with datasets such as Komodo, RAVE, IQVIA, Truven, Optum, or similar Life Sciences and Healthcare datasets.
• You must have hands-on experience building and deploying statistical models and Machine Learning solutions, including segmentation and predictive modeling, hypothesis testing, multivariate statistical analysis, time-series techniques, and optimization.
• You must have proficiency in programming languages and technologies such as Python, SQL, and Spark.
• You should have the ability to work with large datasets and present findings and insights to key stakeholders, along with experience in data management using databases such as SQL.
• You should have experience with at least one major cloud platform, such as AWS, Azure, or Google Cloud, for deploying and scaling language models and AI solutions.

Qualifications

Bachelor’s or Master’s degree in Statistics, Data Science, Applied Mathematics, Business Analytics, Computer Science, Information Systems, or other Quantitative field.