Agile Programming Methodologies, Algorithms, Amazon Web Services (AWS), Analysis Skills, Artificial Intelligence (AI), Artificial Intelligence (AI) Agents, Automation, Business Skills, Cloud Computing, Communication Skills, Continuous Improvement, Data Science, DevOps, Engineering, GCP (Good Clinical Practices), Machine Learning, Performance Analysis, Performance Management, Process Modeling, Requirements Management, Statistics, Thought Leadership, Time Management
Job Description
Role - GEN AI Data Scientist Engineer
Experience Required - 8+ Years
Must Have Technical/Functional Skills
- Machine Learning and Data Science (Expert)
- Strong understanding of core Data Science and Machine Learning concepts.
- Proven experience building, training, validating, and deploying ML models.
- Model deployment experience into production using algorithms and frameworks such as (XGBoost , LightGBM , Scikit-learn)
- Programming and Data Engineering Skills (Expert)
- Statistics and Analytical Skills (Expert)
- Generative AI and Agentic AI Experience (Intermediate)
- Experience with Generative AI concepts and implementation.
- Ability to design and implement AI agents, workflows, tool calling, orchestration, and task automation.
- RAG and Knowledge-Based AI Solutions (Intermediate)
- Cloud Platform Experience (Intermediate) and Hands-on cloud experience. GCP, AWS
- MLOps, DevOps, and Deployment (Intermediate)
Roles & Responsibilities
- ML Process and Model understanding
- Model Deployment & involve in activity for converting in to Agentic solution
- Monitoring & Performance Management
- Security & Compliance
- Continuous improvements
Generic Managerial Skills, If any
- Agile, customer communication and offshore co-ordination and thought leadership ideas
- Communication (Must):
- Candidate must have strong communication skills, with the ability to engage business stakeholders, understand and translate business requirements into technical solutions, and provide timely status updates.
- Ability to interpret model results and communicate findings clearly to technical and business stakeholders.