Operations Analyst (Contract)

We are seeking an AI-fluent operations analyst to help improve business processes, analyse operational data, and support smarter decision-making across the organisation. This role requires strong analytical skills, comfort with AI tools, and the ability to turn data and process insights into practical business improvements. The ideal candidate is proactive, detail-orientated, and excited about using AI to make operations faster, smarter, and more scalable.

Job Title: Operations Analyst

Department: Customer Success Services, Oracle University

Location: Bangalore

Reports To: CSS OU India Director

Role Overview:

We are looking for a detail-orientated and analytically strong operations analyst who is fluent in the use of AI tools and modern automation technologies. This role will support business operations by analysing processes, identifying inefficiencies, building data-driven insights, and using AI to improve productivity, decision-making, and operational performance.

The ideal candidate is comfortable working with data, processes, dashboards, and cross-functional teams. They should also be able to use AI tools effectively for analysis, reporting, workflow automation, documentation, and problem-solving.

Key Responsibilities:

• Analyse day-to-day operational processes, workflows, and performance metrics to identify improvement opportunities.
• Use AI tools to accelerate data analysis, reporting, documentation, research, and process optimisation.
• Build and maintain dashboards, reports, and operational trackers for leadership and business teams.
• Collect, clean, and interpret operational data to identify trends, risks, bottlenecks, and performance gaps.
• Support process improvement initiatives by recommending practical, scalable solutions.
• Work with cross-functional teams to document workflows, standard operating procedures, and business requirements.
• Identify opportunities for automation using AI, no-code/low-code tools, or workflow platforms.
• Prepare executive summaries, business insights, and recommendations based on data analysis.
• Monitor key operational KPIs and provide regular updates to stakeholders.
• Support special projects related to efficiency, cost reduction, productivity improvement, and digital transformation.

AI Fluency Requirements:

The candidate should be confident using AI tools to improve operational efficiency, including:

• Prompting AI tools effectively for research, analysis, summarisation, and content creation.
• Using AI to generate reports, draft SOPs, analyse trends, and improve documentation.
• Understanding how to validate AI-generated outputs for accuracy and business relevance.
• Identifying where AI can reduce manual work or improve process speed and quality.
• Familiarity with tools such as ChatGPT or similar platforms.
• Basic understanding of AI risks, including data privacy, bias, hallucinations, and responsible usage.

Required Skills and Qualifications:

• Bachelor’s degree in business administration, operations, analytics, finance, engineering, or a related field.
• 2–5 years of experience in operations analysis, business analysis, process improvement, or a similar role.
• Strong analytical and problem-solving skills.
• Proficiency in Excel or Google Sheets, including formulas, pivot tables, and data cleaning.
• Experience with reporting or visualisation tools such as Power BI, Tableau, Looker, or similar platforms.
• Strong written and verbal communication skills.
• Ability to work independently and manage multiple priorities.
• Good understanding of business operations, process mapping, and performance measurement.
• Comfortable working with large datasets and translating data into actionable insights.

Key Competencies:

• Analytical thinking
• AI-enabled productivity
• Process improvement mindset
• Strong attention to detail
• Business communication
• Data-driven decision-making
• Cross-functional collaboration
• Curiosity and continuous learning
• Ownership and accountability

Success Metrics:

Success in this role may be measured by:

• Improved operational efficiency and reduced manual work.
• Accuracy and timeliness of reports and dashboards.
• Quality of insights and recommendations provided to leadership.
• Successful implementation of AI-enabled workflow improvements.
• Reduction in process bottlenecks, errors, or delays.
• Stakeholder satisfaction with operational support and analysis.