Sr. AI Threat & Data Management Engineer

Job Description:

Responsibilities

• Manage BANKs assets using AI technology to improve data quality, analysis, and decision-making.
• Leverage advanced analytics methods and technologies-such as machine learning, statistics, optimization, spatial analytics, and AI-to enhance core business processes.
• Contribute to BANKS Data science and AI program and deliver advanced analytics services
• maintenance of a central repository of advanced analytics models and solutions.
• Guide the identification, research, selection, and alignment of technology solutions which meet business and technical requirements for data science and AI.
• Review and approve changes to policies, procedures, and practices related to data science and AI.
• Drive the adoption and integration of machine learning and AI use-cases into regular corporate day-to-day business operations and processes.
• Oversee the management of data science projects from inception to completion. Work closely project stakeholders to define project goals, requirements, deliverables and timelines. This includes allocation of resources, monitor project progress, and mitigate risks, ensuring that projects are delivered on time and within budget.

Qualifications

• Education in Statistics, Computer Science, Engineering or related quantitative fields of study.
• Minimum 5+ years in IT
• 2+ Years in AI
• 3+ Years Azure Cloud
• 3+ Years experience in Threat & Data Management
• Extensive experience with PowerBI
• Extensive experience in multidimensional data modeling; star schemas, snowflakes, denormalized models, handling - slow-changing- dimensions/attributes.
• Understanding of disciplined approach towards Data Visualization and Reporting.
• Experience in setting up complex ETL processes, involving relational and non-relational data.
• Proficiency in machine learning and AI technologies.
• Working knowledge of Out-of-the-box AI services provided by cloud providers (e.g. Azure AI services) to accelerate use-cases related to areas such as natural language processing and data-driven decision-making.
• Experience in areas including data science, statistics, machine learning, data analysis, data integrations (ETL), systems design, maintenance and /or coding.