AI Senior Principal Consultant

at  ARISTON SERVICES PTE LTD

The Senior Principal, AI, Engineering and Governance is a highly experienced and accomplished professional with a deep understanding of Data and AI with governance, engineering, and data science. The ideal candidate will have a proven track record of leading and delivering successful AI and data projects, and will be able to work independently and as part of a team.

Responsibilities:

• Lead pitches, pre-sales and solutioning for AI and data transformation programs across Financial Service, Insurance and other industries.
• Build team of data engineers and data scientists to suite client requirements.
• Lead the development and implementation of data governance policies and procedures.
• Design and build solution of DataOps and MLOps to integrate data from disparate sources.
• Develop and deploy data science models to extract insights from data.
• Work with business stakeholders to understand their data needs and develop solutions that meet those needs.
• Mentor and train junior data scientists and engineers.
• Budget, cost and forecast management.

Qualifications:

• 17-20 years of experience in technology and data management, including AI, ETL, data warehousing, and data mining.
• Strong AI understanding with knowledge of Generative AI and traditional AI Practices
• Strong understanding of data governance principles and practices.
• Experience with a variety of data engineering tools and technologies.
• Experience with a variety of data science tools and technologies.
• Excellent communication and presentation skills.

Interested qualified candidates may send revert along with your updated resume.
Thank you!
Ariston Service

• Lead pitches, pre-sales and solutioning for AI and data transformation programs across Financial Service, Insurance and other industries.
• Build team of data engineers and data scientists to suite client requirements.
• Lead the development and implementation of data governance policies and procedures.
• Design and build solution of DataOps and MLOps to integrate data from disparate sources.
• Develop and deploy data science models to extract insights from data.
• Work with business stakeholders to understand their data needs and develop solutions that meet those needs.
• Mentor and train junior data scientists and engineers.
• Budget, cost and forecast management