Senior Analyst, Quantitative Analytics- Science (PCK333-242681) New York County, New York


AIG has several opportunities for Statisticians to join the rapidly growing Science organization in the Property Casualty business. Recognizing the power of technology, data, and computational science to transform the insurance industry, AIG has formed the Science team consisting of world class business minds and scientists to drive transformational change through evidence-based decision making at the company.

Highly visible and fully supported by the leadership team of the company, the group has a broad and global mandate ranging from solving complex business problems to partnering with leading academicians on the development of next generation modeling techniques. The group’s intent is to be a center of innovation at the company and a catalyst for change.

The group’s mission is both to generate evidence-based insights and to enable improved evidence-based decision making, across AIG. The group has an organizationally broad and geographically global mandate across the company. In addition we lead work outside of AIG such as partnering with leading academicians and understanding exogenous drivers of business results.

Position Summary:
The position of Manager, Quantitative Analytics will require excellence on both technical and communication dimensions. Responsibilities will involve leveraging analytical, synthetic, and quantitative skills in support of our insurance business. The work will revolve around understanding complex businesses, large and complex data manipulation, model building, model validation, and model implementation. The position will require highly effective communication, oral and written.

Organizational Structure and Interface:
The Science team is a highly matrixed organization. While all team members have a senior supervisor, the work is managed in project teams that form, and reform, dynamically as business needs evolve and resolve.

Performance Objectives:
• Build and refine predictive and descriptive statistical models to improve insights, enhance data-driven business strategies, and drive improved profitability
• Build, review, and improve the actual code that solves complex data manipulation problems
• Develop next-generation analytic approaches where current generation approaches are not adequate
• Thoroughly document the thinking and the details to enable future analysts to pick the work up
• Review, direct, guide, inspire the analytical work of more junior staff
• Present updates, insights, and final recommendations with influence to diverse audiences
• Develop material and conduct training for both technical and business colleagues
• Participate in, lead, create cross-functional projects

The Ideal Candidate Has:
• Advanced technical skills for level:
• Advanced quantitative modeling and analytical skills
• Sophisticated synthetic skills enabling identification of important implications
• Statistical skills (such as Confidence intervals, OLS, GLM, Survival, ARIMA)
• Advanced statistical skills (such as MCMC, Bayesian, machine learning, boosting, cross-validation, shrinkage)
• Ability to apply skills to solve weakly structured business problems
• Intermediate to expert knowledge of SAS (Base, Graph, Stat, Macro, ODS, IML)
• Intermediate to expert skills in SQL and experience in using databases from within SAS
• Knowledge of other coding languages such as R, Stata, SPSS, Python, C++
• Experience with Windows and UNIX/Linux operating systems
• General Management Skills:
• Leadership, business acumen, passion for team-oriented work, strategic and creative thinking
• Excellent communication skills with the ability to hear what others are saying and the ability to be heard
• Interest in all aspects of the insurance business and processes (e.g. underwriting, claims adjusting, finance and accounting, risk management and operations)
• Experience in leading projects
• Knowledge of Microsoft Excel and PowerPoint
• 3+ years of experience
• An advanced quantitative degree or equivalent training, skills, and experience

To apply, please click here