S&C Global Network - AI - Hi Tech - Data Science Analyst 2
Accenture (company site, opens in a new tab)2+ yrsBengaluruOn-siteDirect career pageEst. 10–18 LPA
Posted on 25 Sept
Reach people at Accenture
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Accenture you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Develop and fine-tune Generative AI models for NLP, Computer Vision, and multimodal applications using frameworks like LangChain and LlamaIndex.
- Implement scalable data science workflows on cloud platforms such as Azure or AWS, including model training, deployment, and monitoring.
- Perform advanced analytics and develop predictive models, recommendation systems, and optimization solutions using Python, SQL, and machine learning frameworks like TensorFlow or PyTorch.
Minimum Requirements
- Minimum 2 years of experience in data engineering or data science.
- B.Tech or M.Tech degree in Computer Science, Statistics, Applied Mathematics, or related field.
- Proficiency in Python, SQL, and experience with NLP and Computer Vision libraries (e.g., Hugging Face, OpenCV).
- Experience working with cloud platforms Azure and/or AWS for data science workflows.
Ideal Candidate Profile
- Experienced in Generative AI/LLM tooling including model development, fine-tuning, deployment architecture, and autonomous agents.
- Skilled in building and managing data pipelines and scalable cloud-native AI solutions in high-tech domains such as Consumer Tech, Enterprise Tech, or Semiconductors.
- Ability to manage client delivery and stakeholder communication, ideally with exposure to marketing, supply chain, or sales analytics projects.