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
This role is responsible for leading the use of data to make decisions. This includes: the development and recommendation of new machine learning predictive modeling algorithms, the coding/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), and discovery of new business problems that can be solved through the use of machine learning/predictive modeling. The role is responsible for assisting in the recruitment, selection, mentorship and development of junior data scientists. This role will also begin to manage projects of medium to high complexity.
Arity
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-world 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. Arity is committed to supporting an inclusive and diverse environment where you can thrive and learn from others.
The Team
At Arity, our Geospatial Data Science team is a fundamental and key differentiating component of Arity's strategic vision, making transportation smarter, safer, and more useful for everyone. 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 machine learning models to efficiently extract innovative insights from raw GPS and contextual data, enhance applications from enriched geospatial layers on a large scale, and create eye-opening data visualization. By leveraging our state-of-the-art algorithms, cost-effective platform, and easily accessible micro-services, we can quickly turn geospatial data into actionable insights. This team is also fully integrated within a cross-functional scrum team including product owners, software engineers, and other talents to collaborate with for creating innovative products.
The Role
As a machine learning scientist at Arity, you will lead the development of machine learning algorithms primarily on geospatial data. You are expected to make key technical decisions about how to implement machine learning models including both traditional and deep learning models on large volume of geospatial data. You have chances to influence the business for the entire cycle of the ML solution including data collection, processing, aggregation, modeling, and visualization. You will personally prototype the solution development for these projects and work with product owners, data/software engineers, and other partners for productionization and client delivery. Some example projects include:
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Efficiently route match raw GPS data
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Extract mobility patterns from users
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Derive driving behavior based on driving environment
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Build nationwide map quantifying road risk using telematics data
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Dynamic traffic volume forecasting
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Generate synthetic trips
These geospatial insights 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
Your day-to-day looks like:
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Working with large geospatial data sets using distributed computing frameworks
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Building spatial and machine learning models using a variety of libraries/tools and cutting-edge techniques
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Identifying opportunities for new machine learning solutions, exploring new data sources for enrichment, collecting appropriate labels for learning, establishing actionable metrics, and creating reusable model validations and risk mitigation
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Communicating results to key stakeholders in a clear and compelling manner
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Applying appropriate methodologies for the problem and validating the solution with the appropriate metrics
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Establishing and following data science best practices including peer review, code review, documentation, coding standards, and ensuring reproducibility and compliance
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Expanding your machine learning skillset through development opportunities and researching innovative tools and techniques to level up our capabilities
Qualifications
Successful candidates typically have:
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Master’s or PhD degree in a machine learning/AI related field such as engineering, statistics, computer science, physics, or related discipline
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Over 7 years' experience with developing end-to-end machine learning solutions/algorithms including model development, model deployment, model monitoring, and model life-cycle management
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Demonstrated advanced knowledge in predictive models such as parameterized methods, ensemble algorithms, deep neural network, large language models, graph neural networks (GNNs), convolutional networks, transformer architectures
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Experience with scientific computing libraries Scikit-learn, TensorFlow, PyTorch, Spark ML-lib
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Experience with deploying ML models using AI platforms such as Vertex AI and Sagemaker
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Experience with geospatial data is highly preferred, such as US census data, weather data, parcel data, POI, etc
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Ability to process, analyze, and visualize large amounts of geospatial data using Spark/SQL is a plus
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Ability to translate product requirement into well-defined analytical problems
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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
Optional:
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Domain knowledge with transportation models
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Experience with spatial models and techniques such as kriging, spatial linear mixed models, spatio-temporal models, graph theory models
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Experience with image data
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Experience with large language models
Supervisory Responsibilities
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This job does not have supervisory duties.
#LI-JB2
Skills
Algorithms, Artificial Intelligence Markup Language, Business Model Development, Data Analytics, Data Science, Deep Learning, Digital Literacy, Learning Agility, Machine Learning, Neural Networks, Predictive Analytics, Predictive Modeling, Results-Oriented
Compensation
Compensation offered for this role is $121,600.00 – 206,650.00 annually and is based on experience and qualifications.
The candidate(s) offered this position will be required to submit to a background investigation.
Joining our team isn’t just a job — it’s an opportunity. One that takes your skills and pushes them to the next level. One that encourages you to challenge the status quo. And one where you can impact the future for the greater good.
You’ll do all this in a flexible environment that embraces connection and belonging. And with the recognition of several inclusivity and diversity awards, we’ve proven that Allstate empowers everyone to lead, drive change and give back where they work and live.
Good Hands. Greater Together.
Allstate generally does not sponsor individuals for employment-based visas for this position.
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