Data Scientist - Marketing Analytics

Data Scientist

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.

Position Overview

We are seeking a passionate and innovative Data Scientist to join our Marketing Analytics team. This role is responsible for leading the use of data to inform and optimize marketing strategies, customer engagement and business decisions. You will develop and manage machine learning models, build tools that enable data-driven decision-making, and explore new data sources to improve model performance. You'll also manage medium-complexity projects and begin mentoring junior data scientists.

Key Responsibilities

• Conduct rigorous data analysis to uncover trends, patterns, and actionable insights.
• Build and refine data models to support marketing strategy, customer segmentation, and campaign optimization.
• Engineer features and select variables to enhance model performance and scalability.
• Continuously improve model accuracy and relevance by integrating new internal and external data sources.
• Build scalable tools and applications using Python, R, SQL, and Linux environments.
• Lead medium-complexity projects from planning to execution using effective project planning techniques.
• Collaborate with cross-functional teams to implement models and translate insights into actionable business strategies.
• Communicate analytical findings clearly to technical and non-technical stakeholders.

Required Qualifications

• Bachelor's degree in Data Science, Computer Science, Statistics, or a related field.
• 3–5 years of experience in data science, machine learning or analytics.
• Proficiency in Python or R or both.
• Strong understanding of data modeling and data analytics techniques.

Preferred Qualifications

• Familiarity with Azure ML Studio or similar platforms.
• Experience working with insurance industry data or marketing analytics use cases.

Supervisory Responsibilities

This role does not include direct supervisory duties.

Compensation offered for this role is $95,700.00 - 170,925.00 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. One where you can shape the future of protection while supporting causes that mean the most to you. Joining our team means being part of something bigger – a winning team making a meaningful impact.

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.

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, religion, 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.