* Advanced degree in a quantitative discipline, e.g., statistics, applied mathematics, econometrics, economics or operations research * 3+ years of work experience working in a data-centric business environment, preferably within the Insurance industry * Strong consultative communication skills diagnosing Insurance data to develop successful growth strategies with clients * Proven comfort and intellectual curiosity for working with very large sets of data, pulling in relevant team members to address identified - and sometimes undiscovered - client needs * Full fluency in analytic/database management software such as SAS, SQL, SPSS or Access * Strong multi-tasking abilities, flexibility, and patience in a fluid environment * Professional attitude and service orientation; team player * Ability to communicate effectively in English, both verbally and in writing * Willingness to travel
Who You'll Work With
You'll work with our Ingenuity team in Waltham, MA. Ingenuity is part of McKinsey Solutions and McKinsey's New Ventures.
Ingenuity drives significant performance improvement for carriers, reinsurers, and brokers through a combination of advanced analytic capabilities, deep industry knowledge, extensive change management expertise, and the technology infrastructure to develop and host operational solutions. Ingenuity's analytical solutions span the entire insurance value chain including sales/distribution, underwriting/pricing, and claims.
McKinsey New Ventures fosters innovation driven by analytics, design thinking, mobile and social by developing new products/services and integrating them into our client work. It is helping to shift our model toward asset-based consulting and is a foundation for -and expands our investment in -our entrepreneurial culture. Through innovative software as a service solutions, strategic acquisitions, and a vibrant ecosystem of alliances, we are redefining what it means to work with McKinsey.
As one of the fastest-growing parts of our firm, New Ventures has more than 1,500 dedicated professionals (including more than 800 analysts and data scientists) and we're hiring more mathematicians, data scientists, designers, software engineers, product managers, client development managers and general managers.
What You'll Do
You will play a key consultative and client-facing role in the development of big data and advanced analytics as a refined yet evolving capability of our client teams who advise the top firms in the insurance sector.
You will help to shape the future of what data-savvy organizations look like, in part by driving processes for data extraction and analysis, and creating new lines of thinking within our core clients. In this role, you will focus on helping our clients achieve transformational change by designing, developing and executing analytics work streams that serve as the catalyst to creating client impact. One of the core practice priorities is to establish the processes, mindsets & skills required to convert data to business intelligence and insights for our clients. You will not only expand our current Analytics capabilities, but will help architect new strategies and applications within a dynamic and innovative organization.
Leading your team of data scientists, you will work through our clients entire data ecosystems to understand what's available, what's missing - and where to find and collect that information. You will translate the team's findings and work with clients to engage on these and wider issues changing the landscape of the Insurance industry. Additionally, you will develop, implement and maintain effective programs around all elements of data analytics optimization and modeling with a constant eye toward continuous improvement.
McKinsey & Company is an equal opportunity employer. Associated topics: business analyst, capital, commercial, economy asset, estate, financial analyst, gs 0110 12, real estate, valuation, wholesale
* The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.