Sr. IT Business Analyst, Insurance Industry

Sr Anlst IT Bus Analysis - BS07EE
We're determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals - and to help others accomplish theirs, too. Join our team as we help shape the future.

Key Responsibilities

• Guide teams in business analysis best practices, tools, and techniques.
• Act as a liaison between business and IT, ensuring clear communication and alignment.
• Support elicitation efforts by helping teams select effective approaches and identify gaps.
• Adapt techniques in real-time to meet project needs and objectives.
• Mentor team members on emerging analysis methods and generative AI capabilities.
• Design and lead collaborative sessions that drive synergy and achieve outcomes.
• Manage meeting dynamics to ensure focus and productivity.
• Apply strategic thinking to align work with broader organizational goals.

• Strong analytical and critical thinking abilities

• Excellent communication and stakeholder management skills

• Domain expertise in P&C Insurance industry.

• Understand structured, unstructured, and semi structured data and corelate with requirement.
• Ability to craft clear, effective prompts to drive desired outputs from generative models
• Ability to assess and mitigate risks (such as bias) in AI-generated outputs.

• AI enhanced Data Analysis: Ability to use generative AI tools (for example, Microsoft Copilot integrated in Power BI) to transform raw data into actionable insights.

• Requirements Elicitation & Documentation: Leveraging generative AI to automate and enhance the drafting of business requirements, process maps, and reports.

• Prompt Crafting: Designing prompts or agents that help extract domain specific insights from AI systems.

• Prompt Refining (Lifecycle) - Strong skills in prompt engineering and its techniques including design, develop, and refine prompts (zero-shot, few-shot, and chain-of-thought approaches) to maximize the accuracy leverage optimization tools.
• Understanding Bias & Ethics: Awareness of the ethical implications of AI in data analysis, including bias detection and mitigation.