Vice President, Analytics Models & Innovation
$121.9k - $259.7kMarsh
Vice President, Analytics Models & Innovation
Marsh Risk Analytics Solutions is seeking a Vice President to lead digital deployment and integration of our actuarial models and content. Your primary responsibility will be to engage with our digital product development teams and providing expert guidance on actuarial methodologies, model integrations, and product development. You will also be involved in product design, testing, and presenting methodologies to senior internal stakeholders.
This opportunity is well suited to an experienced actuary, statistician, mathematician, or quantitative professional with experience of digital product development. Actuarial credentials are very highly valued but are not required.
We will count on you to:
- Manage model deployment and integration with digital products from planning through delivery. Establish scope, responsibilities, milestones, and deadlines; coordinate analysts and development teams; and proactively resolve methodological gaps, technical questions, and delivery risks.
- Guide product development and integration. Work directly with the digital product development team throughout the product lifecycle to help them understand analytics content, design world-class digital analytics products, and meet development deadlines.
- Be the primary point of contact and subject matter expert for digital analytics content. Educate stakeholders on appropriate methodologies, calculations, and model outputs. Create a strong governance framework around deploying and monitoring analytics content, building test frameworks, challenging use cases, and suggesting alternative approaches.
- Present clear, justified methodology and design decisions. Explain results, uncertainty, and implications for product strategists, analytics leaders, and executive audiences. Develop presentations that connect technical analysis to the decisions our stakeholders need to make.
- Contribute to stakeholder relationships and growth. Partner with colleagues to understand client needs, shape appropriate analytical approaches, and explain our capabilities to existing and prospective clients.
What you need to have:
- Six or more years of relevant technical experience in actuarial analysis, statistics, mathematical modeling, data science, risk analytics, or a related quantitative field.
- A strong foundation in probability, statistics, and quantitative modeling, with the judgment to evaluate assumptions, assess results, and recognize model limitations.
- Significant digital product development experience, or experience deploying models to production environments
- Strong project management skills, including the ability to coordinate contributors, manage competing priorities, and deliver high-quality work against deadlines.
- Clear written and verbal communication skills, with the ability to explain technical concepts and their business implications to nontechnical audiences.
- A collaborative approach to problem-solving, accountability for work quality, and an interest in coaching and developing colleagues.
What makes you stand out:
- Actuarial exam progress toward ACAS or FCAS, or an earned ACAS or FCAS designation. Other actuarial credentials, including ASA or FSA, are also valued.
- Insurance experience, particularly in property and casualty, loss modeling, insurance program evaluation, or risk financing.
- Software development experience, particularly developing analytics tools and products
- Experience with stochastic modeling, Monte Carlo simulation, predictive modeling, or retained-loss analysis.
Why join our team?
We help you be your best through professional development opportunities, interesting work and supportive leaders. We foster a vibrant and inclusive culture where you can work with talented colleagues to create new solutions and have impact for colleagues, clients and communities. Our scale enables us to provide a range of career opportunities, as well as benefits and rewards to enhance your well-being.
We welcome applicants from actuarial, statistics, mathematics, and other quantitative backgrounds. If you meet the core requirements, we encourage you to apply even if you do not meet every preferred qualification.
Marsh (NYSE: MRSH) is a global leader in risk, reinsurance and capital, people and investments, and management consulting, advising clients in 130 countries. With annual revenue of over $27 billion and more than 95,000 colleagues, Marsh helps build the confidence to thrive through the power of perspective. For more information, visit marsh.com, or follow us on LinkedIn and X.
Marsh is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age background, disability, ethnic origin, family duties, gender orientation or expression, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, veteran status (including protected veterans), or any other characteristic protected by applicable law. If you have a need that requires accommodation, please let us know by contacting View email address on click.appcast.io. Marsh is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one “anchor day” per week on which their full team will be together in person. The applicable base salary range for this role is $121,900 to $259,700.The base pay offered will be determined on factors such as experience, skills, training, location, certifications, education, and any applicable minimum wage requirements. Decisions will be determined on a case-by-case basis. In addition to the base salary, this position may be eligible for performance-based incentives.
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