Operations and Data Assistant

Key Responsibilities

• Support data collection, preparation, and consolidation from multiple internal and external data sources across business functions.
• Assist in maintaining data accuracy, consistency, and integrity through data cleaning, validation, and basic quality checks.
• Perform exploratory and routine data analysis to identify trends, patterns, and data anomalies under senior guidance.
• Support the development, testing, and monitoring of AI and machine learning models, including preparation of training datasets and performance outputs.
• Assist with the implementation and maintenance of data analytics and AI frameworks, tools, and standards aligned with company and global data governance practices.
• Support data governance, privacy, and security requirements, ensuring compliance with internal policies and applicable regulations.
• Contribute to the measurement, tracking, and reporting of data and AI performance metrics, ensuring outputs are accurate and audit-ready.
• Develop and maintain dashboards, visualizations, and reports using approved BI tools (e.g., Power BI, Tableau) for internal stakeholders.
• Develop and maintain AI Agents to automate tasks with key corporate functions.
• Provide analytical inputs to business teams, project teams, and leadership to support operational and strategic decision-making.
• Assist in responding to ad‑hoc data requests, audits, internal reviews, and client or stakeholder data queries.
• Collaborate with the operations teams to support AI-driven initiatives and projects.
• Support the continuous improvement of data analytics processes, tools, and documentation.

Requirements & Tech Stack

• Foundational proficiency in Python, SQL, or R.
• Experience in developing AI Agents.
• Familiarity with data visualization or BI tools (e.g., Power BI, Tableau) is desirable.

Qualifications

• Bachelor’s degree (or in progress) in Data Analytics, Computer Science, Statistics, Mathematics, AI, or a related field.
• Internship, academic projects, or entry-level experience in data or analytics is preferred.
• Basic understanding of data analysis, statistics, and machine learning concepts.
• Strong analytical and problem-solving skills with high attention to detail.
• Strong communication skills (oral and written) with the ability to present data clearly when supported by senior team members.
• Ability to work collaboratively in a matrixed, professional environment.
• Proactive, organized, and eager to learn emerging AI and data technologies.
• Good interpersonal skills, communication skills (oral & written) with a strong client-centric and commercially aware approach.
• Exposure to data analysis, reporting, or AI tools within a corporate, consulting, technology, or professional services environment is preferred.
• Basic experience supporting data governance, reporting, or analytics initiatives under supervision.