Vice President - Insurance Analytics


India - Bangalore


15 Years - 25 Years



Job Application

Accepting Applications

Job Description

- Delivery:The incumbent will be responsible to lead the Analytic delivery for leading Insurance provider by managing the key SLAs like service level, quality, customer satisfaction, utilization, attrition etc
- P&L Management Support and grow the business consistently & profitably to achieve an organization with growth of people and turnover with target profit margins
- People Management: Should have considerable experience in managing large analytics teams (100+ members)
- Client management: Should have experience in managing clients, multiple stakeholders and engage proactively to ensure best in class service delivery and identify farming opportunities.
- Growth pipeline: Support the growth pipeline process through active engagement and execution support for new opportunity areas. Ensure formulation and achievement of goals, strategy, structure, staffing, skills, style and processes are synergistic with the verticals objectives / super ordinate goal
- Solution design support: Engage with internal stakeholders, existing and new clients to understand their requirements and translate these into a solution framework. This will entail creative thinking abilities and an ability to interpret unstructured requirements
- Project based execution support: Help incubate new engagements by executing Pilot, Proof of Concept projects to establish capabilities and credibility with existing and new clients. This may entail working either as an independent analyst or as part of a larger team to deliver on client requirements
- New capabilities development:Prepare white papers and undertaking proof of concepts on data available with the existing support teams. This will also include providing analytics support to the Operations teams
- Best practice sharing: participate in translating analytics best practices across different customer accounts and aid capability building for the Insurance R&A practice. This may also entail helping build domain and technical capabilities within the team and vertical through training support

Ideal Candidate & Qualifications

- 15-17 years Insurance analytics experience with very good exposure to various functions within anInsurance Company
- Ability to undertake drill down analysis of key business problems and interpret results, generate insights and recommend strategies
- Ability to translate business problems into most efficient and effective analysis plan; Should be able to manage and mentor the team working on the analysis including data pull, data preparation and build statistical models using SAS / R /other statistical tools
- Excellent communication and interpersonal skills and proven ability to manage large teams
- Conceptual, analytical & tactical thinking, strategic thought process
- Exposure to analytical modeling in the Insurance domain is desirable/being numerate is essential
- Excellent written and oral communication skills
- Excellent interpersonal skills, with the ability to develop strong working relationships and effectively influence all levels of business stakeholders
- Ability to naturally assume ownership of initiatives, requiring minimal supervision to consistently deliver outstanding results
- Ability to manage multiple stakeholders across different geographies. Familiar with US & Europe markets

Core Functional Responsibilities & Domain Expertise

Analytics Focus should be on identifying broad analytic leadership skills rather than having deep data science specialization/hands on experience.

1. Analytic thought leadership and consulting skills (partnering with the spokes to design/develop solutions)
2. Broad knowledge of the analytic services, tools, methodologies and how to build analytic delivery capabilities
3. Experience in building and managing analytic teams that execute a wide range of service delivery
4. Understanding and experience driving solutions that cover various levels of analytic
5. Insights and decision support (dashboards, spreadsheet solutions, etc.)
6. business analysis root cause, segmentation, simple non-predictive analytics, business performance improvements
7. advanced analytics using traditional methods (simple to complex modeling)
8. advanced analytics using data science/machine learning (complex modeling/NLP with structured/unstructured data)
9. View is that recent/deep hands on experience in all of the above areas are less critical. Not data scientists in the modern sense (i.e. may not program in Python for example). Leader needs to be knowledgeable and capable of forming a team with those skills represented effectively through his/her direct reports and 2-down as needed rather than being a deep expert/doer in all of these areas themselves.
10. Has extend the capabilities both toward more insights/decision support/business analysis as well as complex analytics/data science
11. Ability to tell the story from the analysis regardless of whether its a simple business segmentation or a complex machine learning model
12. Understanding of data and technology tools/platforms and how those enable analytic delivery

Domain expertise
1. P&C insurance is preferred if possible but understand the market constraints
2. If no P&C insurance, other insurance or financial services is a strong preference with specialization in life insurance or credit/lending/banking that have risk underwriting elements and non-intermediary distribution models
3. Experience working with extensive and complex data


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