Business Analyst - Field Operations & Customer Success

Business Analyst Field Operations & Customer Success

AI-First Business Analysis | Client-Facing | Field Operations

About the Role:

We are building an AI-powered platform that helps hotels identify and recover significant VAT refund opportunities. As a Business Analyst, you will work directly with premium hotels, understand their business operations, gather operational data, identify gaps, and help customers successfully adopt our platform.

This is a client-facing role requiring a combination of business analysis, field operations, customer interaction, and problem-solving.

AI-first is the working default for this role: every assessment, BRD, insight, and customer-facing report should start with AI augmentation. If a task is being done manually that an AI tool could do faster and better, that is treated as a process gap, not a personal workstyle choice.

Key Responsibilities:

Customer Engagement:

- Visit hotels and meet stakeholders.

- Build relationships with Finance, Operations, Revenue, and Hotel Management teams.

- Understand existing operational workflows.

- Gather business requirements and process information.

Business Analysis:

- Analyse hotel operational processes.

- Identify gaps affecting VAT recovery.

- Convert business requirements into structured documentation.

- Author BRDs that are specific and complete enough for the product/engineering team to build from directly, without needing a translation layer.

- Use AI tools (ChatGPT, Claude, or equivalent) to accelerate data analysis, pattern identification, and first drafts of BRDs and reports and document the workflow so it is repeatable.

- Recommend process improvements.

Field Operations:

- Conduct on-site assessments.

- Validate operational data.

- Collect supporting information required for implementation.

- Coordinate with customers during onboarding.

Product Adoption:

- Demonstrate platform capabilities.

- Explain business value to customers.

- Guide customers through implementation.

- Resolve customer queries during onboarding.

- Push back professionally on customer requests that fall outside scope or feasibility using data and evidence, without damaging the relationship.

Cross-functional Collaboration:

- Work closely with Product, Engineering, Sales, Operations, and Customer Success teams.

- Share customer feedback for continuous product improvement.

- Support implementation and rollout activities.

- Flag recurring customer asks or customisation requests that could signal a broader product/feature need, rather than a one-off fix.

Reporting:

- Prepare business reports and implementation updates.

- Present findings and recommendations to internal teams and customers.

- Track project progress and customer outcomes.

- Maintain simple trackers/dashboards for assessments, onboarding status, and VAT recovery outcomes built as decision tools, not just record-keeping.

- Contribute client outcome data (recovery value, adoption progress) that can be used to build value/ROI summaries for customers.

Required Skills:

Must Have:

- Excellent communication and presentation skills.

- Strong analytical and logical thinking.

- Customer-facing confidence.

- Problem-solving mindset.

- Ability to travel locally for customer meetings.

- Ability to challenge customers professionally using data and insights.

- Comfortable using AI tools (ChatGPT, Claude, or equivalent) as part of daily analysis and documentation work.

- Ownership mindset.

- Fast learner.

Good to Have:

- Experience in Business Analysis, Customer Success, Consulting, Hotel/Hospitality, SaaS, FinTech, or ERP/CRM Implementation.

- Exposure to BRD/FRD writing, or basic dashboarding (Excel, Tableau, Power BI).

Preferred Qualification:

Bachelor's Degree (Any discipline). MBA is a plus but not mandatory.

Success Metrics (KPIs):

- Customer meetings completed.

- Business requirements documented.

- Hotel assessments completed.

- Customer onboarding success rate.

- Implementation completion rate.

- Customer satisfaction score.

- Product adoption rate.

- Quality of business insights submitted.

- Percentage of analysis/documentation output that is AI-augmented (tracked as a growing baseline, not a one-time metric).