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Senior Data Scientist
Allstate
Chicago, IL, United States
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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. Our team uses data to make decisions about real problems, from building predictive models to developing new machine learning techniques. We’re passionate about learning new disciplines and skills to deliver top-notch 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
Data scientists at Arity use data to make decisions, working closely with data engineers, developers, and product managers. As part of a product team, you’ll develop new predictive models, code and develop tools to make business decisions, integrate external and internal data to improve our modeling results, and more. 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. Success in this role depends on your ability to manage complex projects and adapt quickly to the needs of the business.
Responsibilities
• Prepare and perform analyses, including data acquisition, data cleansing and transformation, model validation, implementation, documentation, and clearly communicates results
• Build and implement statistical models through best practices to address business needs and improve results
• Manage data and data requests to improve the accuracy of our data and decisions made from data analysis
• Learn and use a variety of tools and languages to achieve results (e.g., Python, Spark, SQL, R)
• Identify statistical algorithms and tools that can make our models more accurate and our team more efficient
• Collaborate with the team to improve the effectiveness of business decisions using data and predictive modeling
• Understand key problems facing the telematics, insurance, and transportation industries to identify the optimal loss modeling approach
• Tailor communication about loss models to team members, leadership, and stakeholders to ensure a common understanding
• Effectively plan projects by breaking down moderately complex initiatives into tasks; ensure deadlines are kept
• Work with leaders to ensure projects meet their needs
• Develop and execute a communication strategy, with appropriate coaching, that keeps all relevant stakeholders informed and provides opportunities to influence the direction of the work
• Review and evaluate the suitability of techniques, given current loss modeling practices, and communicate a position to senior leadership
• Lead and participate 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 using statistical modeling and/or machine learning techniques to build models that have driven company decision making
• Experience building and evaluating Generalized Linear Models (GLMs)
• Experience managing and manipulating large, complex datasets
• Experience performing exploratory data analysis
• Experience working with statistical software such as SAS, SPSS, MatLab, R, CART, etc.
• Ability to write queries in SQL
• Ability to code and manipulate data in a language such as Python, Perl, Java, C
• Knowledge of advanced modeling techniques
• Ability to analyze and interpret moderate to complex concepts
• Ability to provide written and oral interpretation of highly specialized terms and data and to present this data to others with varying levels of expertise
• Demonstrated analytic agility
• Demonstrated ability to communicate across multiple levels of leadership
Good to have:
• Actuarial background, pricing, or loss modeling experience
• Experience in the insurance industry; an understanding of the insurance marketplace, economic atmosphere, and regulatory environment
• Experience working with statistical methods other than GLMs
• Experience working with insurance loss and exposure data
• Master’s or PhD in a quantitative field such as statistics, mathematics, computer science, finance, or economics
• Experience working with mobile sensor data
• Experience working through end to end life cycle from data acquisition, model building through to deploying, monitoring and revising models in a production setting
• Experience working with big data, NOSQL, or PySpark
• Strong programming background
It is the policy of Allstate to employ the best qualified individuals available for all jobs without regard to race, color, religion, sex, age, national origin, sexual orientation, gender identity/gender expression, disability, and citizenship status as a veteran with a disability or veteran of the Vietnam Era.