Data Scientist Consultant II

• Develop and maintain data-driven solutions that improve business decision making
• Participate in the full analytics lifecycle, including data acquisition, exploratory analysis, model development, deployment support, monitoring, and communication of results
• Collaborate with the Managing Data Scientist, team members, cross-functional partners, and business stakeholders
• Apply statistical, machine learning, and emerging AI techniques to solve business problems
• Improve decision making through analytics, machine learning, and AI-driven solutions
• Plan projects, break work into manageable tasks, and deliver against established timelines
• Explore, prepare, and analyze data sources to support modeling and business insights
• Contribute to 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 analytical methods, data sources, and technologies
• Participate in code reviews, knowledge sharing, and adoption of team best practices

Requirements

• Legal right to work in the UK; 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
• Experience applying statistical, machine learning, and data analysis 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: experience developing predictive models in a business environment
• Desirable: exposure to cloud platforms such as Azure or AWS
• Desirable: experience supporting deployed analytics, machine learning, or AI solutions
• Desirable: experience using AI-assisted development tools such as GitHub Copilot, Claude Code, or similar technologies
• Desirable: exposure to LLMs, generative AI, AI agents, or agent orchestration frameworks
• Desirable: familiarity with CI/CD, containerization (Docker), or software engineering best practices
• Desirable: exposure to model governance, risk management, or MLOps practices
• Desirable: experience with PyTorch, TensorFlow, R, or similar technologies
• Desirable: Master’s degree in a quantitative or technical discipline, or equivalent practical experience

Core Competencies

Demonstrates expertise in developing and maintaining data-driven solutions using Python, machine learning, and AI techniques to enhance business decision-making. Proficient in the full analytics lifecycle, including data acquisition, model development, and deployment support.

Highest-signal resume keywords

• Python Programming
• Machine Learning Techniques
• Data Analysis
• Statistical Modeling
• Cloud Platforms (Azure, AWS)

Hard Skills

• Data Acquisition
• Model Development
• Exploratory Analysis
• AI Techniques
• Predictive Modeling
• Statistical Analysis
• Data Preparation
• ML Solutions Deployment
• CI/CD Practices
• Containerization (Docker)

Soft Skills

• Problem-Solving
• Communication
• Collaboration
• Continuous Learning
• Independence

Certifications & Qualifications

• Master’s Degree in Quantitative Discipline

Industry Keywords

• MLOps
• Model Governance
• Risk Management
• Generative AI
• Agent Orchestration

Tools & Technologies

• AI-Assisted Development Tools
• GitHub Copilot
• PyTorch
• TensorFlow
• Claude Code