Arity - Geospatial Data Science Manager

At Allstate, great things happen when our people work together to protect families and their belongings from life’s uncertainties. And for more than 90 years our innovative drive has kept us a step ahead of our customers’ evolving needs. From advocating for seat belts, air bags and graduated driving laws, to being an industry leader in pricing sophistication, telematics, and, more recently, device and identity protection. 

Job Description

Arity was founded by The Allstate Corporation, which means we have the same innovative mindset that drives us to put the needs of our customers first. We collect and analyze enormous amounts of data in order to provide cutting-edge solutions to organizations invested in improving transportation

Arity’s Geospatial team uses advanced machine learning and AI to develop insights and data products from huge volumes of driving data from phones and other IoT devices. By understanding user behavior and intent through personal mobility patterns, analyzing and forecasting traffic flow, and identifying road infrastructure opportunities that reduce driving risk, our insights help make transportation smarter and safer for everyone. We are a team of geospatial data scientists that use expert knowledge of maps, mobility patterns, and modern, advanced data science techniques to create value through innovative data products provide across multiple industries and help Arity deliver on its core mission.

The Role:

We are looking for a Sr. Manager to lead our Geospatial team in developing the world’s leading mobility analytic insights to be deployed through Arity’s internal and customer-facing data products.  The ideal candidate is results oriented and has a proven track record of leading greenfield machine learning research from design through iterative development to implementation in production.  You will lead a team of diverse and talented data scientists, setting priorities, advising on methodology, ensuring consistent progress is made toward goals, and managing relationships with key Product and Engineering stakeholders to ensure successful deployment of models. You will be responsible for team member recruitment, selection, and people management, and you will play an active role in team and department strategy development.

Responsibilities:

• Builds & evolves vision and strategy for using machine learning/predictive modeling and optimization to deliver valuable features that support our product roadmap

• Builds alignment for vision and strategy with Product and Engineering partners, fostering relationships and engaging resources across departments

• Leads managers and expert individual contributors, builds and develops team dedicated to executing data science initiatives to increase organizational value

• Effectively understands business problems, requirements, and context in communicating findings to ensure solutions are well understood and incorporated into products

• Develops and executes communication strategy, keeping stakeholders informed, and influencing business partners and senior leaders.

• Collaborates with and influences partnering Product and Engineering teams in deploying models into production.

• Identifies potential solutions that use new areas of data, research, and models

• Utilizes project planning techniques to break down complex and occasionally highly complex machine learning/predictive modeling and/or development projects into tasks, manages scope of projects, develops project plans, and ensures deadlines are kept.

• Trains, develops, and teaches team

• Serves as subject matter expert and consultant on data and analytics related issues inside and outside the department

Required Qualifications:

• Bachelor’s degree in a quantitative field such as statistics, mathematics, computer science, finance, or economics 

• 7 or more years of professional experience

• Proven track record of delivering results, leading teams in the development and deployment of machine learning models to production to solve business and technical problems

• Demonstrated experience working with large, complex datasets and machine learning methodologies

• Familiarity with commonly used data science tools and libraries in Python, R, Java, Scala, C

• Familiarity with commonly used geospatial data querying technologies

• Demonstrated domain expertise in geospatial analytics

• 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

• Ability to manage a wide range of loosely defined moderate to complex situations, which require application of crea