Data Scientist- Hybrid

Job description

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. Your role in the team This role is responsible for leading the use of data to make decisions, with a focus on supporting the Casualty business through predictive modeling and machine learning solutions. 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 mentorship and development of junior data scientists. This role is also accountable for informing the strategy of the department and will begin to manage complex projects as an individual contributor. Key responsibilities: Uses best practices to develop complex statistical and machine learning techniques to build models that address business needs, including Casualty-related outcomes such as claim severity, disputes, settlement strategy, and operational efficiency. Reviews, evaluates, communicates and makes recommendations on the appropriateness of modeling techniques and results to the team, leadership and stakeholders to ensure these are well understood and incorporated into business processes. Develops and executes communication strategy, keeps stakeholders informed, and influences business partners and senior leaders on the effectiveness of machine learning/predictive modeling to solve business problems, including the ability to explain technical information clearly to non-technical partners. Utilizes effective project planning techniques to break down complex machine learning/predictive modeling and/or development projects into tasks, manages scope of projects, develops project plans, and ensures deadlines are kept. Manages analytical and modeling projects with a small number of team members and is expected to work independently with customers after initial onboarding. Supports, mentors, and coaches junior data scientists and team members as needed. Collaborates with and influences business units, including design teams and Casualty partners, to improve the effectiveness of business decisions and business results through designing, building, and partnering to implement machine learning/predictive models. Effectively understands business problems and requirements to identify the optimal modeling approach and build alignment within the department. Identifies languages and tools that can bring efficiencies or needed techniques to the team, including Python, SQL, R, and preferred exposure to AWS or Azure cloud environments. Identifies and develops solutions that use new areas of data, research and models, and develops data sources that can solve business problems. Essential Skills: A minimum of 4 years of data science, machine learning, predictive modeling, and/or querying data experience Hands on experience with Python, SQL, and/or R Experience building or applying machine learning/predictive models to solve business problems Ability to query data and work with databases/data sources Ability to explain technical information clearly to non-technical stakeholders Ability to work independently with customers after initial onboarding Desirable Skills: Master’s Degree in a highly quantitative field such as mathematics, physics or computer science Experience working in the insurance industry Supervisory Responsibilities: This job does not have supervisory duties. Posting date: Monday 27th July 2026 [11.59pm] #LI-SE1 #LI-Hybrid Skills Artificial Intelligence Markup Language, Business Data Analytics, Business Model Development, Data Analysis, Data Analytics, Data-Driven Decision Making, Data Science, Machine Learning (ML), Machine Learning Algorithms, Mathematics, Predictive Modeling, Strategic Management Shape the Future of Insurance with Cutting-Edge Tech and a People-First Culture Why join us? Allstate NI is proud to be Allstate’s European Digital Centre of Excellence, a hub for innovation and engineering excellence. We’re recent winners of Best Place to Work in IT (100+ employees) and Best Use of Cloud Services at the Belfast Telegraph IT Awards, and we’ve been recognised for our community and sustainability impact with Platinum in the Northern Ireland Environmental Benchmarking Survey. We’re a product-driven, cloud-first organisation delivering real outcomes through modern technology, a digital product-centric talent model, and a culture rooted in engineering excellence. Our teams work in cross-functional structures, guided by an outcome-based delivery approach that accelerates speed, agility, and value. We also invest in you. At Allstate NI, your career growth matters. You’ll have access to our Continuous Learning Hub, designed to support skills development and professional advancement through tailored learning paths, certifications, and mentoring opportunities. Whether you’re deepening technical expertise or exploring leadership roles, we provide the tools and support to help you thrive. What do you get in return? As well as receiving a competitive annual salary, our reward package includes: Corporate bonus scheme Pension scheme Annual performance-related pay reviews Life assurance and income protection Flexible working options Hybrid working Private medical and dental insurance Access to an employee assistance programme Discounted gym membership Two paid volunteering days each year Cycle to work scheme Be part of a high-performing, socially responsible organisation where your work has purpose, and your growth is supported every step of the way.