Educational Requirements (any of the following):
- Bachelor of Engineering/Bachelor of Technology in any stream with consistent academic track record.
- Bachelor's degree in a quantitative discipline (e.g., Operation Research, Statistics, Mathematics) or significant relevant coursework with consistent academic track record. Additional Academic Qualification (good to have):
- Masters in any area related to Science, Operation Research, Mathematics and Statistics with consistent academic track record.
- PhD in any stream.
- Understand the requirements from the business and translate it into an appropriate technical requirement.
- Responsible for successful delivery of MLOps solutions and services in client consulting environments;
- Define key business problems to be solved; formulate high level solution approaches and identify data to solve those problems, develop, analyze/draw conclusions and present to client.
- Assist clients with operationalization metrics to track performance of ML Models
- Help team with ML Pipelines from creation to execution
- Guide team to debug on issues with pipeline failures
- Understand and take requirements on Operationalization of ML Models from Data Scientist
- Engage with Business / Stakeholders with status update on progress of development and issue fix
- Setup Standards related to Coding, Pipelines and Documentation
- Research on new topics, services and enhancements in Cloud Technologies
- Good knowledge on software configuration management systems
- Strong business acumen, strategy and cross-industry thought leadership
- Awareness of latest technologies and Industry trends
- Logical thinking and problem solving skills along with an ability to collaborate
- Two or three industry domain knowledge
- Understanding of the financial processes for various types of projects and the various pricing models available
- Client Interfacing skills
- Knowledge of SDLC and agile methodologies
- Project and Team management