About the Role

As part of the GSS DAS team, you will help drive the execution of AI and advanced analytics initiatives that improve business operations and decision-making. You will work closely with cross-functional teams including Operations, Product, Data Science, and Engineering to support the development and rollout of AI-powered solutions.

This role is ideal for someone who is curious about AI, enjoys solving business problems using data, and can effectively coordinate across teams to drive execution. - What the Candidate Will Do -

• Support execution of AI and analytics initiatives through effective coordination with cross-functional teams.
• Assist in gathering business requirements and supporting AI and analytics use cases.
• Build and maintain AI-powered tools, automations, and workflows to improve team productivity and operational processes.
• Work with datasets to identify trends, generate insights, and support business decision-making.
• Collaborate with technical and business teams during development, testing, and rollout of AI-enabled solutions.
• Track project updates, action items, and deliverables across ongoing initiatives.
• Build dashboards, reports, and analyses to monitor performance and project impact.
• Document processes, workflows, and best practices to support operational efficiency.
• Identify opportunities for process improvement and automation across day-to-day workflows.

- Basic Qualifications -

• Minimum 1+ years experience working in business intelligence, analytics, data engineering, or a similar role.
• Proficiency in writing and optimizing SQL queries for data extraction and feature engineering pipelines.
• Foundational experience using Python for data manipulation and preparation of datasets to support AI/ML models.
• Exposure to AI/ML models and familiarity with building or utilizing AI agents (e.g., no-code tools like Copilot).
• Strong influence and relationship management skills; comfortable interacting across all levels of stakeholders.
• Fluency in communicating analytical methods, results, and recommendations to peers and partner teams.
• Demonstrates strong ownership, attention to detail, and a proactive approach to managing assigned tasks.
• Ability to effectively collaborate with cross-functional and remote teams.

- Preferred Qualifications -

• BS / MS degree equivalent experience in Statistics, Economics, Engineering, or other quantitative fields.
• Programming background and expertise in solving a business problem using Python or similar programing languages
• Experience of successfully managing small to medium-scale projects
• Familiarity with the end-to-end AI/ML model lifecycle, including feature engineering, model evaluation metrics, and deployment pipelines.