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
ArityAs an advertising data scientist at Arity, you will lead the development of machine learning algorithms on both 1st party driving data like GPS and driving events, as well as, ad platform data including impressions, clicks, conversions. You are expected to make key technical decisions about how to implement machine learning models including both traditional and deep learning models on large volumes of data. You have chances to influence the business for the entire cycle of the optimization solution including data collection, processing, modeling, A/B testing on the ad platform. You will personally prototype these solutions and work with product owners, data/software engineers, and other partners for productionization and KPI measurement. Some example projects include:
Click-through rate (CTR)/conversion prediction
Win rate model
Dynamic bidding strategy
Pacing control and budget management
Frequency capping model
Platform simulation
These models help us understand how effective our ad platform is and provide opportunities for improvement and growth. 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:
Be a thought partner in the area of experimentation for Ads Platform, and autonomously identify and pursue research with significant business impact on KPIs
Analyzing large amount of data sets using distributed computing frameworks
Building advanced algorithm and machine learning models using a variety of libraries/tools and cutting-edge techniques
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
Communicating results to key stakeholders in a clear and compelling manner
Establishing and following data science best practices including peer review, code review, documentation, coding standards, and ensuring reproducibility and compliance
Working with product and engineering partners for model handoff and productionization
Qualifications
Successful candidates typically have:
Master’s or PhD degree in a machine learning/AI related field such as engineering, statistics, computer science, physics, or related discipline
5+ years of industry experience in data science, data analytics, and machine learning in advertising domain
Deep experience in digital advertising including systems, measurement sciences, and principled incrementality approaches and passion for incentive challenges
Experience with ad auctions (RTB platform) such as dynamic bidding strategy, ad ranking, and experimentation on the advertising platform
Advanced knowledge in predictive models such as parameterized methods, ensemble algorithms, deep neural network, and reinforcement learning algorithms such as multi-armed bandit algorithms, Q-learning, deep reinforcement learning
Demonstrated experience using Python and Spark for big data query/processing and engineering skills for productionizing the solution
Experience with scientific computing libraries Scikit-learn, TensorFlow, PyTorch, and Spark ML-lib
Over 5 years' experience with developing end-to-end machine learning solutions/algorithms including model development, deployment, monitoring, and life-cycle management on the advertising platform
Ability to translate product requirement into well-defined analytical problems and produce feasible solutions
Ability to provide written and oral interpretation of highly specialized terms and data, and ability to present this data to stakeholders with different levels of expertise
Optional:
Experience with control theory and the application to ad platform optimization
Experience with cloud data warehouse solutions such as BigQuery or Redshift
Experience with deploying ML models using AI platforms such as Vertex AI and Sagemaker
Experience with geospatial data is preferred, such as US census data, weather data, parcel data, POI, etc
Skills
Algorithms, Big Data, Data Analytics, Data Science, Deep Learning, Digital Advertising, Machine Learning, Machine Learning Algorithms, Predictive ModelingCompensation
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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Yearly based
USA - IL (Remote)