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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.