Risk Analytics Data Scientist
- Employer
- Allstate Insurance Company
- Location
- Nationwide
- Salary
- Not Specified
- Closing date
- Sep 23, 2019
View more
- Category
- Actuary, Risk Management
- Job Type
- Not Specified
- Career Level
- Not Specified
Job Details
Where good people build rewarding careers.
Think that working in the insurance field can’t be exciting, rewarding and challenging? Think again. You’ll help us reinvent protection and retirement to improve customers’ lives. We’ll help you make an impact with our training and mentoring offerings. Here, you’ll have the opportunity to expand and apply your skills in ways you never thought possible. And you’ll have fun doing it. Join a company of individuals with hopes, plans and passions, all using and developing our talents for good, at work and in life.
Job Description
Risk analytics spans a broad set of empirically-based disciplines (applied statistics, econometrics, applied mathematics, algorithmics / optimization, and machine learning / data science) applied to and across all the major risk silos (credit, market, operational, liquidity, and model risk). We are seeking analysts in these fields to apply their training and experience to optimize risk-and-return business decisions in the Performance and Analytics team within Allstate’s Enterprise Risk and Return Management group. We place a premium on expert statistical and econometric programming skills/experience with real-world data (e.g. SAS, Matlab, Python, SPSS, R, C++). The Risk Analytics Data Scientist is responsible for aligning with and contributing to corporate objectives by identifying and developing growth and profitability opportunities that will enable Allstate to generate profitable market share growth. He/she is accountable for using data and non-trivial statistical/econometric code that in most circumstances, seamlessly and directly translates into material business decisions for the firm. This includes building predictive models and developing original-yet-defensible methods that enable Allstate to make better decisions and win in the marketplace.
This role is responsible for leading the use of data to make risk-and-return analytics decisions. This includes the development and management of predictive modeling and the design and development and vetting of original methodology; statistical/econometric empirically-based coding expertise in at least one major relevant language is required (e.g. SAS, Matlab, Python, SPSS, R, C++) as this will serve as the basis by which the abovementioned business decisions are made.
Key Responsibilities
-
Uses best practices to implement and develop statistical, econometric, and machine learning techniques to build risk analytics models that directly address material business needs.
Peer reviewed publications & related awards are highly valued / desired, as are technical conference decks.
Academic honors, top standardized test scores, scholarships and fellowships are highly valued / desired.
Incorporates independent replication and model validation methods into the model development process and understands the necessity for this, as well as the extreme efficiency gains that result from this best practice.
Works on data and complex business problems to drive improved risk-and-return business decisions and results by designing, building, and partnering to implement the right models for the right problems.
Can identify new areas of data, research and methodology/models that can solve relevant risk-and-return business challenges.
Collaborates the with team to understand the business’ problems to identify the optimal methodological, and modeling (method+language/platform), approaches.
Job Qualifications
- Master’s or PhD degree preferred, or concentration in a quantitative field such as statistics, econometrics/economics, data science, applied mathematics, computer science, and/or finance.
- Best-of-breed expertise in working with statistical software such as SAS, MatLab, Python, SPSS, R, C++.
- Demonstrated expertise using statistical and econometric modeling and/or machine learning techniques to build models that have driven company decision making.
- Demonstrated experience incorporating independent replication and model validation methods into the model development process.
- Demonstrated experience and ability developing and executing non-siloed, cross-disciplinary solutions to complex, real-world, non-textbook business challenges.
- Demonstrated ability and experience to provide both written and oral interpretation of highly specialized terms and data, and to present to others with varying levels of expertise to achieve ‘buy-in’ to the right approaches.
- Knowledge of modeling techniques, and the experience to know how to select, apply, and test the right models for the right problems.
The candidate(s) offered this position will be required to submit to a background investigation, which includes a drug screen.
Good Work. Good Life. Good Hands®.
As a Fortune 100 company and industry leader, we provide a competitive salary – but that’s just the beginning. Our Total Rewards package also offers benefits like tuition assistance, medical and dental insurance, as well as a robust pension and 401(k). Plus, you’ll have access to a wide variety of programs to help you balance your work and personal life -- including a generous paid time off policy.
Learn more about life at Allstate. Connect with us on Twitter, Facebook, Instagram and LinkedIn or watch a video.
Allstate generally does not sponsor individuals for employment-based visas for this position.
Effective July 1, 2014, under Indiana House Enrolled Act (HEA) 1242, it is against public policy of the State of Indiana and a discriminatory practice for an employer to discriminate against a prospective employee on the basis of status as a veteran by refusing to employ an applicant on the basis that they are a veteran of the armed forces of the United States, a member of the Indiana National Guard or a member of a reserve component.
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Company
- Website
- https://www.allstate.com/
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