Arity-Data Scientist-Claims Analytics Allstate
Chicago, IL

Job Description

Founded by The Allstate Corporation in 2016, Arity is a data and analytics company focused on improving transportation. We collect and analyze enormous amounts of data, using predictive analytics to build solutions with a single goal in mind: to make transportation smarter, safer and more useful for everyone.

At the heart of that mission are the people that work here-the dreamers, doers and difference-makers that call this place home. As part of that team, your work will showcase both your intelligence and your creativity as you tackle real problems and put your talents towards transforming transportation.

That's because at Arity, we believe work and life shouldn't be at odds with one another. After all, we know that your unique qualities give you a unique perspective. We don't just want you to see yourself here. We want you to be yourself here.

The Team

Arity Data Science & Analytics combines technical knowledge in fields such as mathematics, computer programming, and data engineering with business expertise. We're passionate about learning new disciplines and techniques to deliver top-notch predictive analytics products. Armed with billions of miles of driving data, we constantly challenge ourselves to seek out opportunities for new products and ways to make our existing offerings better. Our purpose is to extract meaning from data to make Arity's vision of safer, smarter, and more useful transportation a reality.

The Role

This role will be part of the Insurance Solutions product area, working to develop telematics-based insights to aid in the claims handling process, and potentially for other insurance use-cases for telematics beyond pricing and claims. All data scientists across product teams at Arity are responsible for leading the use of data to make decisions, including:

* The development and management of new machine learning predictive models
* The coding and development of tools that use machine learning/predictive modeling to make business decisions
* Searching for and integrating new data (both internal and external) that improves our modeling and machine learning results (and ultimately our decisions)
* Discovery of solutions to business problems that can be solved through the use of machine learning/predictive modeling

As an ideal candidate, you appreciate the difference between fitting and implementing statistical models, the importance of good metrics, and the significance of large-volume high-quality data. You can perceive common structure between superficially unrelated problems, and can use this to build tools, algorithms, and products of high value. This role will also begin to manage projects of medium complexity.

Responsibilities

* Uses best practices to develop statistical, machine learning techniques to build models that address business needs
* Manages data and data requests to improve the accuracy of our data and decisions made from data analysis
* Uses and learns a wide variety of tools and languages to achieve results (e.g., R, SAS, Python, Hadoop)
* Identifies languages and tools that can bring efficiencies or needed techniques to the team
* Works on data and business problems to drive improved business results through designing, building, and partnering to implement models
* Collaborates with the team to improve the effectiveness of business decisions through the use of data and machine learning/predictive modeling
* Understands the business' problems to identify the optimal modeling approach
* Communicates to team members, leadership and stakeholders on findings to ensure models are well understood and incorporated into business processes
* Utilizes effective project planning techniques to break down moderately complex projects into tasks and ensure deadlines are kept
* Works with leaders to ensure the project will meet their needs
* The development and execution of a communication strategy, with appropriate coaching, that keeps all relevant stakeholders informed and provides an opportunity to influence the direction of the work
* Reviews and evaluates on appropriateness of techniques, given current modeling practices, to senior leadership
* Leads and participates in peer reviews, code reviews and other department activities

Qualifications

Required:

* Degree in a quantitative field such as statistics, mathematics, computer science, finance or related discipline
* Experience in managing and manipulating large, complex datasets
* Experience in working with statistical software such as SAS, SPSS, MatLab, R, CART, etc.
* Ability to code and develop prototypes in languages such as Python, Perl, Java, C
* Knowledge of advanced modeling techniques, experience in using statistical modeling and/or machine learning techniques to build models
* Ability to provide written and oral interpretation of highly specialized terms and data, and ability to present this data to others with different levels of expertise
* Demonstrated analytic agility

Preferred:

* 3+ years of insurance industry experience
* Experience developing models to help with claims handling