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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist Consultant II - (Hybrid) - **Company:** Allstate - **Location:** Belfast, UK - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Data Analysis, Microsoft Azure, Software Quality, Code Review, Continuous Integration, Information Engineering, Programming Tools, R (Programming Language), Python (Programming Language), Machine Learning, Tensorflow, Software Construction, GitHub Copilot, Pytorch, Large Language Models, Multi-Agent Systems, Generative AI, Containerization, Data Analytics, Machine Learning Operations, Docker - **Published:** September 4, 2026 - **Apply:** https://uk.indeed.com/viewjob?jk=70df74792ace517d ## About the Role All applicants must demonstrate they have a legal right to work in the UK for employment at Allstate. Allstate is not providing sponsorship for this vacancy. * Minimum of 2 years of hands-on experience using Python to solve analytical, data science, machine learning, or data engineering problems. * Foundational understanding of statistics, machine learning, and data analysis techniques, with experience applying those concepts to real-world business, academic, or personal projects. * Strong problem-solving, communication, and collaboration skills. * Ability to independently execute well-defined work while seeking guidance appropriately. * Demonstrated willingness to continuously learn and adopt new tools, technologies, and ways of working. Desirable Skills: * Experience developing predictive models in a business environment. * Exposure to cloud platforms such as Azure or AWS. * Experience supporting deployed analytics, machine learning, or AI solutions. * Experience using AI-assisted development tools such as GitHub Copilot, Claude Code, or similar technologies. * Exposure to LLMs, generative AI, AI agents, or agent orchestration frameworks. * Familiarity with CI/CD, containerization (Docker), or software engineering best practices. * Exposure to model governance, risk management, or MLOps practices. * Experience with additional analytical tools or frameworks such as PyTorch, TensorFlow, R, or similar technologies. * Master's degree in a quantitative or technical discipline, or equivalent practical experience., Business Case Analyses, Data Analytics, Data Engineering, Data Science, Predictive Analytics, Predictive Modeling, Python (Programming Language), Waterfall Model ## Description This role contributes to the development and maintenance of data-driven solutions that improve business decision making. Working closely with the Managing Data Scientist and cross-functional partners, the individual will participate in the full analytics lifecycle, including data acquisition, exploratory analysis, model development, deployment support, monitoring, and communication of results. The role is expected to apply statistical, machine learning, and emerging AI techniques to solve business problems while continuing to build technical depth and business understanding. The successful candidate will demonstrate growing independence in project execution, curiosity for learning new technologies, and the ability to collaborate effectively with both technical and non-technical stakeholders. Key responsibilities: * Collaborate with team members and business partners to improve decision making through analytics, machine learning, and AI-driven solutions. * Apply statistical and machine learning techniques to develop models and analytical solutions that address business needs. * Utilize effective project planning techniques to break work into manageable tasks and deliver against established timelines. * Explore, prepare, and analyze data sources to support modeling and business insights. * Contribute to the development, testing, deployment, and monitoring of ML and AI solutions. * Evaluate, communicate, and document modeling approaches, results, assumptions, and recommendations for technical and non-technical audiences. * Leverage modern development tools, including AI-assisted coding solutions, to improve productivity and code quality. * Research and experiment with new analytical methods, data sources, and technologies to improve team capabilities and business outcomes. * Collaborate with peers through code reviews, knowledge sharing, and adoption of team best practices. ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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