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

Founded by The Allstate Corporation in 2016, Arity is a fully remote 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.

Arity Core Telematics

Arity’s Core Telematics team uses advanced machine learning and AI to translate huge volumes of sensor data from phones and other IoT devices into insights about driving.  We are an applied research team that develops the fundamental intelligence that fuels all of Arity’s products, from crash detection to risky behaviors like distracted driving to passenger detection and more.  We use our deep understanding of sensor technologies, vehicle physics, and cutting-edge deep learning techniques to tackle the most challenging and exciting problems that help Arity achieve its mission.

The Role

We are looking for an expert data scientist to lead an R&D team in developing the world’s leading crash detection algorithms, which will be deployed through our partners to offer life-saving services to millions of users.  The ideal candidate has extensive experience in designing and implementing optimal deep learning architectures on time series data from sensors/IoT devices and significant experience working with software engineers to deploy models on the edge.  You will act as a player-coach, responsible for both individual technical contributions and providing project leadership and technical direction to junior data scientists on highly complex technical projects.  Your knowledge and expertise will also be relied upon for team member recruitment, selection, and mentorship, and you will play an active role in team and department strategy development.

Responsibilities

• Uses best practices to develop highly complex deep learning architectures to build models that improve the accuracy of our crash prediction algorithms running on time series data from mobile phone sensors and other IoT devices.

• Reviews, evaluates, communicates, and makes recommendations on the appropriateness of deep learning methods to the team, leadership, and stakeholders to ensure these are well understood and incorporated into business processes.

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

• Collaborates with and influences partnering business and engineering teams in deploying models into production mobile apps/SDKs.

• Understands the business problem domain and requirements to identify the optimal modeling approach.

• Develops and builds alignment within the department for frameworks/prototypes that integrate data and machine learning to make business decisions.

• Identifies languages and tools that can bring efficiencies or needed techniques to the team.

• Identifies and develops solutions that use new areas of data, research and models and develops data sources that can solve business problems.

• 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

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

• Demonstrated experience in building and deploying deep learning models to production to solve business and technical problems

• Demonstrated experience in managing and manipulating large, complex datasets

• Proven ability to code and develop prototypes in various languages, such as Python, R, Java, Scala, C

• Proven experience developing deep learning models using common industry frameworks, such as TensorFlow, PyTorch, Keras, MXNet, Caffe, ONNX, etc.

• 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 creativity and originality, where guidance and counsel may be unavailable

• Ability to lead a project team of various skills levels

Preferred Qualifications

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

• Proven experience in developing cutting-edge deep learning architectures and training models on sensor/IoT time series data

• Proven experience deploying deep learning models to the edge with commonly used frameworks such as TensorFlow Lite, PyTorch Mobile, CoreML

#LI-JB2

Skills

Business Data Analytics, Computer Science, Data Science, Deep Learning, Machine Learning, Machine Learning Algorithms, Predictive Analytics, Predictive Modeling, Python (Programming Language), PyTorch

Compensation

Compensation offered for this role is $134,400.00 – 217,350.00 annually and is based on experience and qualifications.

The candidate(s) offered this position will be required to submit to a background investigation, which includes a drug screen.

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.

Effective July 1, 2014, under Indiana House Enrolled Act (HEA) 1242, it is against public policy of the State of Indiana and a discriminatory practice for an employer to discriminate against a prospective employee on the basis of status as a veteran by refusing to employ an applicant on the basis that they are a veteran of the armed forces of the United States, a member of the Indiana National Guard or a member of a reserve component.

For jobs in San Francisco, please click “here” for information regarding the San Francisco Fair Chance Ordinance.
For jobs in Los Angeles, please click “here” for information regarding the Los Angeles Fair Chance Initiative for Hiring Ordinance.

To view the “EEO is the Law” poster click “here”. This poster provides information concerning the laws and procedures for filing complaints of violations of the laws with the Office of Federal Contract Compliance Programs

To view the FMLA poster, click “here”. This poster summarizing the major provisions of the Family and Medical Leave Act (FMLA) and telling employees how to file a complaint.

It is the Company’s policy to employ the best qualified individuals available for all jobs. Therefore, any discriminatory action taken on account of an employee’s ancestry, age, color, disability, genetic information, gender, gender identity, gender expression, sexual and reproductive health decision, marital status, medical condition, military or veteran status, national origin, race (include traits historically associated with race, including, but not limited to, hair texture and protective hairstyles), religion (including religious dress), sex, or sexual orientation that adversely affects an employee's terms or conditions of employment is prohibited. This policy applies to all aspects of the employment relationship, including, but not limited to, hiring, training, salary administration, promotion, job assignment, benefits, discipline, and separation of employment.