- Solid knowledge and experience of supervised, unsupervised and reinforcement learning machine learning algorithms
- Experience with the current state of AI/ML, Large Language Models, and Generative AI
- Finetune language models to specific domains using LLM to improve the accuracy and effectiveness of textbased applications
- Build generative AI models that can generate original content, such as text, images, or music
- Experience with model explainability and interpretability techniques
- Experience in machine learning frameworks and tools ( For e
- Advanced level programming in SQL and Python/Pyspark to guide teams
- Lead and manage a team of data scientists and engineers working on generative AI projects
- Identify and evaluate new AI technologies and tools that could be leveraged for generative AI projects.
- Understand the nuances between traditional Machine Learning lifecycle and Generative AI modeling lifecycle
- Develop and implement ethical guidelines and standards for AI development and deployment
- Stay up to date with the latest research and trends in the field of generative AI and apply them to the company's projects and goals Communicate effectively with stakeholders at all levels of the organization to explain the benefits and risksof generative AI solutions
- Data Science
- Candidates' should have real time client exposure on Healthcare OR CPG domain.
- Only Updated resumes should be proposed along with project experience
- Min 15 years of Full time education is must (BE / B.Tech / MCA / M.Sc / M.E / M.Tech / MBA) Full Time
Data Scientist - Bangalore/Mumbai/Hyderabad/Kolkata, India - iimjobs
Description
Data Science - Director - CPG DomainDiversity Profiles only will be considered
Job Description:
g:
classifiers, cluster analysis, dimension reduction, regression, and models CNN, RNN, DQN, GAN, temporal difference methods, sequence modeling, NLP/NLU, word/doc embeddings, collaborative filtering, self-attention, transformers, etc.
g:
scikit-learn, mlr, caret, H2O, TensorFlow,MXNet, Pytorch, Caffe/Caffe2, CNTK, MLlib)