Arity - Data Science Intern

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 Analytics Team 

At Arity, our Data Science team is at the core of helping us transform mobility. We not only know how to analyze and find meaning within billions of miles of driving data collected from smartphones, onboard devices and third parties; 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 to make transportation smarter, safer, and more useful for everyone. 

Where good people build rewarding careers. 

This Summer 2025 internship is for students currently enrolled in a graduate degree program. This role is responsible for the use and development of data science/geospatial projects and proof of concept business solutions for users in Analytics and Data Science. This person partners with Data Scientists and Data Engineers to provide tactical solutions in one of the several product segments including insurance, geospatial enrichment, core telematics, and advertising. This is a highly dynamic position that requires a great degree of flexibility, analytic agility and the ability to rapidly adapt to changing business requirements/needs, new technologies and data sources. This role requires close integration and partnership with the business and Data Science team and requires business acumen in order to output the best technical solutions.  

Job Description  

• Uses best practices, with limited coaching, to develop machine learning and geospatial techniques to build models that address business needs 

• Utilizes effective project planning techniques to break down basic and occasionally moderately complex projects into tasks and ensure deadlines are kept 

• Uses and learns a wide variety of tools and languages to achieve results (e.g., Python, Spark, SQL) 

• Collaborates with the team in order to improve the effectiveness of business decisions through the use of data and machine learning/predictive modeling 

• Innovates on projects by using predictive modeling techniques, deep learning techniques or tools 

• Executes on modeling/machine learning projects effectively 

• Reviews and evaluates on appropriateness of techniques, given current modeling practices, to senior leadership 

Job Qualifications  

• Target Start date: May/June 2025 

• Currently pursuing a master or PhD degree (strongly preferred) in a quantitative field (e.g. mathematics, statistics, computer or physical science) 

• Ability to solve problems, think critically, and communicate clearly 

• Knowledge of statistical modeling, machine learning, mathematical optimization, and/or data mining from graduate level course work 

• Proven capability of executing end-to-end analytics projects from capstone projects, research projects, or past intern experience 

• Demonstrated fluency with Python or R programming 

• Experience with Spark or AWS computing services such as EMR, Glue, Sagemaker or data warehouse service like BigQuery is a plus 

• Understanding of algorithmic scaling and complexity is a plus