Arity-Data Scientist (Remote-Home Based Worker)

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

At Arity, our Data Science team is at the core of helping us transform mobility. Not only do we know how to analyze and find meaning within billions of miles of driving data collected from smartphones, onboard devices and third parties, but we are passionate about how it affects the end-users of our products. On our team, people get the opportunity to build scalable distributed data pipelines, develop and deploy an array of machine learning algorithms, and create eye-opening data visualizations. We find top talent from various quantitative disciplines to collaborate with product owners, software engineers, and experience designers in development teams to create innovative products that make transportation smarter, safer, and more useful for everyone. 

The Role

As a Senior Data Scientist at Arity, you will help lead the use of data to drive decisions at scale. You will collaborate with product owners, data & software engineers, and designers to develop and deploy robust, scalable services that enhance our understanding of user mobility. You will create new ways of finding meaning from our unique combination of driving and mobility data along with insurance, shared mobility, and mobile app data that help us understand transportation and the risk of behaviors on the road. You will also help shape and grow our culture we have worked hard to establish – promoting recognition of good work, continuous learning, winning together, and having fun along the way. 

Responsibilities 

Building machine learning models using a variety of languages and tool sets to detect driving behaviors and leverage them to understand user mobility

Working with large data sets using distributed computing frameworks

Working cross-functionally to identify business opportunities for data science, collecting appropriate labels for learning, establishing actionable metrics, and creating reusable model validations and risk mitigation

Communicating results to key stakeholders in a clear and compelling manner

Applying appropriate methodologies for the problem and validating the solution with the appropriate metrics

Establishing and following data science best practices including peer review, code review, documentation, coding standards, and ensuring reproducibility and compliance

Expanding your data science skillset through development opportunities and researching innovative tools and techniques to level up our capabilities 

Qualifications

Experience driving complex data science projects from ideation through to completion, typically gained through at least a few years of experience in a similar role

Degree in a quantitative field such as statistics, mathematics, computer science, finance or related discipline

Ability to code and develop prototypes in languages such as Python, R, Matlab, Scala, SQL, SAS etc.

Ability to translate business problems into well-defined analytical problems

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

Experience in managing and manipulating large and complex datasets in both relational databases and distributed environments (e.g. Hadoop)

Experience in using statistical modeling and/or machine learning techniques to build models that have driven company decision-making 

Optional: 

Master’s or PhD degree in a quantitative field such as statistics, mathematics, computer science, finance, or related discipline

Experience working through end-to-end life cycle from data acquisition, model building through to deploying, monitoring and revising models in a production setting