This role will be responsible for translating analytics and generating insights from data with high level of autonomy Individual is expected to have strong technical expertise in data science and analytics space generating insights from data and providing solutions to the business as needed
Principal Responsibilities
Execute clinical and operation advanced analytics that facilitates gaining deep insight to clinical and operation data for relevant business partners in Global Development GD and clinical therapeutic areas
Develop novel data science methodologies to generate deep insights from disparate data sources
Provide subject matter expertise to teams in identification and application of the right data science methodology for a business problem
Formulate the right business problem in collaboration with business and create necessary analysis plans
Develop machine learning methodologies both supervised and unsupervised as appropriate to the business problem
Develop and apply statistical modeling methodologies including predictive and exploratory approaches to generate insights and support evidencebased decision making
Understand legacy R pipelines help refactor and develop scalable and robust code in R or Python in support of data science projects
Ensure the life cycle management of the models is maintained through code repositories and version control tools
Perform data engineering data preprocessing and data wrangling activities utilizing different approaches such as SQL NOSQL graph models
Good understanding of Natural Language Processing methodologies
Establishing an internal and external benchmarking network facilitating the distillation of best data integration and analytics practice from leading organization externally while also identifying best practice from internal teams within JJ
Pretrain fine tune and prompt engineering understanding leveraging LLMs
Design evaluate and implement Generative AI solutions leveraging large language models LLMs embeddings vector databases RetrievalAugmented Generation RAG and agentic workflows to solve clinical and operational business problems
Establish evaluation benchmarking and validation frameworks for statistical models machine learning solutions and GenAI applications to ensure performance robustness and business impact
Partner with Global Clinical Development business stakeholders SMEs and technology teams to identify opportunities where statistical analytics machine learning and GenAI can create value
Education and Experience Requirements
Individual should have a minimum of 2 years with relevant masters or Bachelors degree in data science statistics Informatics operations research computer science engineering or information systems or a related discipline OR A minimum of 1 years with a PhD degree in data science statistics Informatics operations research computer science engineering or information systems is required
Other Relevant Experiences and Skills
Proven ability to translate and influence business requirements against existing analytics and data integration capabilities whilst identifying capabilities challenges and necessary solutions to ensure realistic goal setting for future analytics modelling A proven record in shaping and delivering key programs that optimized performance and delivered project support in matrix environments is required
Experience in advanced analytics processes including gaining insight from structured and unstructured data predictive modelling and optimization and associated systemsdatabase infrastructure
Solid working knowledge of traditional statistical methodologies
Strong working knowledge of statistical modeling techniques including regression classification survival analysis experimental design and predictive analytics
Strong working knowledge of machine learning methodologies both supervised and unsupervised learning methods
Experience applying and evaluating Generative AI technologies including LLMs prompt engineering embeddings vector databases RetrievalAugmented Generation RAG and multimodal AI systems
High proficiency in one of the programming languages R and statistical pipelines
Familiarity of best practices in machine learning model development validation and deployment
Familiarity with evaluation and benchmarking methodologies for machine learning and GenAI solutions including model validation performance assessment and AI governance principles
Solid understanding of life cycle management of the code and code repositories
Extensive experience with data wrangling data preprocessing and data engineering techniques on large datasets
Technical expertise preferably in pharmaceutical clinical or a regulated industry operation with extensive ex
Skills
Mandatory Skills : AI/Generative AI, Data science, ML & geospatial, Python - Data Science, Python for DATA, Statistics-Data Science
Good to Have Skills : Python, Python AI
About LTM
LTM is an AI-centric global technology services company and the Business Creativity partner to the world’s largest and most disruptive enterprises. We bring human insights and intelligent systems together to help clients create greater value at the intersection of technology and domain expertise. Our capabilities span integrated operations, transformation, and business AI — enabling new ways of working, new productivity paradigms, and new roads to value. Together with over 87,000 employees across 40 countries and our global network of partners, LTM — a Larsen & Toubro company — owns business outcomes for our clients, helping them not just outperform the market, but to Outcreate it. Please also note that neither LTM nor any of its authorized recruitment agencies/partners charge any candidate registration fee or any other fees from talent (candidates) towards appearing for an interview or securing employment/internship. Candidates shall be solely responsible for verifying the credentials of any agency/consultant that claims to be working with LTM for recruitment. Please note that anyone who relies on the representations made by fraudulent employment agencies does so at their own risk, and LTM disclaims any liability in case of loss or damage suffered as a consequence of the same.