Manager / Sr. Manager - Actuarial_Pricing

PRICING MANAGER

Department	Actuarial
Reports To	Lead Pricing Actuary
Location	Mumbai, Maharashtra

The Opportunity

We are seeking a Pricing Manager who can combine actuarial and statistical rigour with healthcare economics, product thinking, automation and strong written communication. The role will support the design, pricing, implementation and ongoing management of retail and group health products, including indemnity, benefit-based and OPD propositions.

The successful candidate may come from insurance or from an adjacent analytical industry, provided they can demonstrate strong pricing or risk-modelling capability, healthcare or consumer-economics understanding, disciplined model governance and the ability to learn health insurance concepts quickly.

Key Responsibilities

• Build, refine and govern pricing models for retail, group, indemnity, fixed-benefit and OPD products, with transparent assumptions, reproducible calculations, version control and clear documentation.
• Analyse claim frequency, severity, utilisation, provider costs, medical inflation, loss ratios, expenses, persistency, customer behaviour and portfolio mix; distinguish credible evidence from judgement and proxy assumptions.
• Develop premium calculators and rating algorithms; explain pricing logic to Product, Underwriting and Technology teams; define business rules, prepare independent test cases, support system implementation and provide pricing sign-off.
• For OPD propositions, assess consultation, diagnostics, pharmacy, dental, vision and preventive-care utilisation; evaluate benefit limits, network discounts, cashless versus reimbursement behaviour, anti-selection, misuse and affordability.
• Assess the financial impact of product features, underwriting rules, discounts, loadings, deductibles, co-payments, sub-limits, waiting periods, network arrangements and benefit-design changes.
• Perform scenario, sensitivity, stress, elasticity and profitability analyses and translate outcomes into clear product, pricing and risk recommendations.
• Prepare high-quality actuarial technical notes, pricing papers, governance submissions, rate tables and responses to internal or regulatory queries. Reports must state the purpose, data, methodology, assumptions, limitations, results, risks and recommendation clearly.
• Establish post-launch monitoring through actual-versus-expected analysis, cohort and segment views, leading indicators and trigger-based corrective actions, including repricing or product redesign.
• Automate recurring analyses, controls and reporting using fit-for-purpose tools such as Python, SQL, R, VBA or workflow platforms; reduce manual intervention while retaining audit trails and review controls.
• Challenge conventional approaches and generate practical alternatives by connecting customer needs, healthcare delivery, provider economics, data and technology. Convert ideas into testable hypotheses, pilots or minimum viable analytical solutions.
• Partner with Product, Underwriting, Claims, Finance, Distribution, Operations, Provider Network, Data and Technology teams to deliver implementable solutions from concept through launch and monitoring.
• Review team output, coach junior colleagues and promote consistent standards for modelling, peer review, documentation and knowledge sharing.

Candidate Profile

Experience and education

• Typically, 8 to 10 years of relevant experience in pricing, actuarial analysis, healthcare analytics, risk modelling, revenue management, product economics or a similar quantitative field.
• Meaningful progress toward an actuarial qualification is preferred for candidates from insurance. Candidates from outside insurance may instead demonstrate strong credentials in statistics, econometrics, data science, healthcare economics, operations research, finance, engineering or a related quantitative discipline.
• Prior people-management experience is useful but is less important than demonstrated ownership, review capability and the ability to influence cross-functional teams.

Core technical capabilities

• Strong grounding in probability, statistics, predictive modelling, segmentation, forecasting, scenario analysis and model validation.
• Advanced Excel capability, including structured and controlled model design. Practical proficiency in at least one automation or analytical stack such as Python and SQL, R and SQL, SAS, or an equivalent modern platform.
• Ability to create reproducible data pipelines, automated checks, dashboards and management reports; familiarity with source control, testing and documentation is desirable.
• Understanding of pricing economics, unit economics, demand and utilisation behaviour, cost drivers, margins and portfolio trade-offs.
• For insurance candidates, knowledge of Indian health insurance products, pricing, filing and regulatory expectations. For non-insurance candidates, demonstrated ability to learn regulated product environments and translate adjacent experience into insurance applications.

Health and OPD domain capabilities

• Ability to understand healthcare pathways and cost components across hospitalisation and OPD services, including consultation, diagnostics, pharmacy and provider-network economics.
• Ability to model frequency, severity and utilisation, including seasonality, chronic-care patterns, provider variation, medical inflation, anti-selection, moral hazard and benefit-induced utilisation.
• Ability to connect product design with customer value, affordability, operational feasibility, provider arrangements, data availability and sustainable profitability.

Communication, judgement and innovation

• Excellent report-writing skills, with the ability to produce concise, logically structured and decision-oriented technical and executive papers.
• Ability to explain complex models, assumptions and uncertainty to non-technical stakeholders without losing technical accuracy.
• Strong critical-thinking and problem-framing skills: clarifies the decision required, identifies missing evidence, challenges weak assumptions and prioritises material issues.
• Creative and commercially grounded thinking: looks beyond established insurance practices, adapts methods from other industries and proposes practical, controlled experiments.
• High attention to detail, ownership, integrity and a strong control mindset, with comfort working through ambiguity and competing priorities.

Relevant Backgrounds Outside Insurance

We welcome candidates from adjacent sectors where pricing, healthcare utilisation, consumer behaviour or data-driven product economics are central.

• Healthcare consulting, hospital or provider analytics, pharmacy, diagnostics, health-tech, digital health or third-party administration.
• Consumer lending, payments, fintech or credit-risk analytics, particularly where candidates have built controlled pricing or risk-decision models.
• E-commerce, travel, telecom, subscription businesses or revenue management, where candidates have worked on demand elasticity, segmentation, dynamic pricing or unit economics.
• Pharmaceutical market access, health economics and outcomes research, epidemiology or public-health analytics.
• Management consulting, data science or advanced analytics roles involving product strategy, pricing, forecasting and executive communication.

Candidates from outside insurance should be able to demonstrate transferable evidence in four areas: quantitative pricing or risk modelling; healthcare or consumer-economics understanding; automation and reproducibility; and clear written recommendations for senior decision-makers.

What Success Looks Like

• Accurate, timely, auditable and well-documented pricing outputs.
• Clear recommendations that distinguish evidence, assumptions, uncertainty, limitations and management judgement.
• Pricing models and calculators that are implementable, independently testable and supported by robust controls.
• Useful OPD and health-portfolio insights that inform product design, provider strategy, affordability and sustainable profitability.
• Measurable reduction in manual effort through automation, without weakening governance or review.
• Constructive challenge, practical innovation and effective cross-functional delivery from concept through post-launch monitoring.
• Improved capability and consistency across the pricing team.

Preferred Evidence During Selection

• A concise sample report or pricing recommendation showing analytical structure, judgement and executive communication.
• A practical case study covering an unfamiliar health or OPD pricing problem, including assumptions, data gaps, methodology, risks and recommendation.
• A demonstration or explanation of an automation solution built by the candidate, including controls, testing, documentation and impact.
• An example of a non-obvious idea that was converted into a practical analytical or product solution.