Technical Business Analyst II

Mployee.me; Hyderabad; Hybrid; INR 1,400,000 - 2,400,000; Full time

Job summary

Swiss Res Life Health Reinsurance is seeking a Technical Business / Product Analyst to bridge business strategy, data intelligence, and AI-enabled delivery in Hyderabad. You will transform complex requirements into actionable specs and collaborate with actuarial, underwriting, operations, and technology teams to deliver trusted AI-powered products.

The role emphasizes rigorous testing, real-world business alignment, and driving adoption across production environments.

Qualifications

• Hands-on SQL for data analysis, validation, and investigation.
• Strong data analysis skills across business metrics and outcomes.
• Experience translating business needs into technical requirements and tests.

Responsibilities

• Business Analysis: define MVP scope and shape AI-enabled product ideas.
• Data AI Enablement: validate model outputs, dashboards, and reasoning workflows.
• Quality Assurance Testing: design and execute functional test scenarios and lead UAT.
• Delivery Production Support: participate in go-live readiness and post-launch support.

Skills

SQL

Data analysis

Stakeholder mgmt

AI concepts

Job description

Job Summary

Technical Business / Product Analyst - Life Health Re

Location: Hyderabad, India

Are you energised by the intersection of data, AI, and real-world business impact Do you thrive on turning complex problems into elegant, trusted solutions If you are a sharp analytical thinker with a passion for quality and a curiosity for what AI can do next - this role was built for you.

Role Overview

This is a pivotal role at the heart of Swiss Res Life Health Reinsurance transformation. As a Technical Business / Product Analyst, you will sit at the crossroads of business strategy, data intelligence, and AI-enabled delivery - helping shape the future of how LH Re operates. You will work with brilliant minds across actuarial, underwriting, operations, and technology to bring AI-driven products from concept to production, ensuring every solution is business-aligned, rigorously tested, and genuinely trusted by the people who use it.

Key Responsibilities

Business Analysis Product Shaping

• Build and nurture trusted relationships with internal LH business partners across underwriting, in-force management, operations, and actuarial functions
• Collaborate with stakeholders to brainstorm ideas, shape use cases, and define MVP scope aligned with the long-term AI product vision
• Capture and translate complex business requirements into clear, actionable functional and non-functional specifications
• Ensure requirements reflect real business value, usability, and operational realities - not just technical feasibility

Data AI Enablement

• Analyse business problems using data-driven approaches, including hands-on SQL-based analysis and structured analytical thinking
• Partner closely with AI and data teams to ensure model outputs, recommendations, and reasoning workflows align with business expectations
• Support validation of AI-enabled insights, dashboards, and decision-support workflows from a business and functional perspective
• Leverage exposure to AI/GenAI concepts, including prompt engineering, to bridge the gap between business intent and technical execution

Quality Assurance Testing

• Define and execute functional test scenarios for data, analytics, and AI-enabled solutions with rigour and precision
• Lead UAT and functional testing cycles, ensuring solutions meet agreed business requirements before go-live
• Analyse functional defects, identify root causes, and collaborate with delivery teams to drive resolution
• Champion high-quality releases through structured test planning, execution, and sign-off processes

Delivery Production Support

• Step up during peak cycles, bringing flexibility and dependability when critical deadlines demand it
• Support defect resolution, production incident analysis, and problem management with a calm, solutions-oriented approach
• Participate in go-live readiness activities, including validation, stakeholder sign-offs, and post-launch support
• Act as a trusted business-facing contact during early production usage, driving adoption and ensuring solution stability

About the Team

Life Health Data Analytics Engineering is a strategic technology partner for Swiss Res Life Health Reinsurance division - and we are just getting started. Sitting at the forefront of transforming the data landscape, the team builds innovative analytical products and capabilities that enable better, faster, data-driven decisions across the entire business value chain. As part of the broader Advance with AI initiative, the team is actively building and delivering AI-driven capabilities across end-to-end LH operations and in-force management - leveraging Swiss Res rich global data foundation and enterprise business applications to enable continuous portfolio monitoring, actionable insights, and reasoning-enabled workflows in a regulated environment. This is a team that moves with purpose, thinks boldly, and builds things that matter.

About You

You are a naturally curious, detail-oriented professional who brings both analytical depth and strong interpersonal skills to everything you do. You are equally comfortable diving into a dataset and presenting findings to a senior business stakeholder. You take quality seriously - not as a checkbox, but as a mindset. You are adaptable, collaborative, and motivated by the idea of making AI work in the real world, responsibly and effectively.

We are looking for candidates who meet these requirements:

• 5-7 years of hands-on business analysis and data analysis experience, with a strong functional testing and quality assurance background within complex data or technology environments
• Hands‑on SQL experience for data analysis, validation, and investigation of data-driven solutions
• Life Health insurance or reinsurance domain knowledge, with the ability to understand and articulate complex business processes and translate them into clear technical requirements

These are additional nice to haves:

• Experience supporting AI-driven decision support or monitoring solutions, ideally within a regulated industry
• Exposure to in‑force management, portfolio analytics, or underwriting workflows within a Life Health context
• Familiarity with AI/GenAI concepts, including prompt engineering, model governance, or explainability frameworks
• Experience navigating large, global enterprise environments with cross-functional, agile delivery teams
• Knowledge of regulatory expectations around data, model risk, or analytics in financial services
• Strong stakeholder management and communication skills, with the ability to engage confidently across technical and non‑technical audiences

Our company has a hybrid work model where the expectation is that you will be in the office at least three days per week.