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Frontline Insurance is a property and casualty insurance company in the United States providing customizable solutions to customers for over 25 years. In the past 5 years, we have diversified our information technology team abroad seeking talented individuals in the UK with the opening of our Belfast office.
The Frontline Insurance UK team brings new technologies and insights to the US market with a focus on data science and machine learning, data analytics, platform development, and project management to augment Frontline Insurance's operations and competitiveness in the US Insurance Industry.
We seek a Data Scientist to join our team and help build our data science platform and technologies. You will have the opportunity to enter a green field environment and put your mark on creating solutions that are:
- Dedicated to improving the digital customer experience
- Apply machine learning and AI technologies to provide customized solutions for our policy holders, enabling cost savings while improving the company’s risk exposure
- Improving our business teams efficiencies with the use of advanced machine learning platforms
- Use of industry leading intelligent technologies
- Add to our culture of innovation and creativity
The Role
We are looking for a Data Scientist with strong experience in applying traditional machine learning and AI techniques alongside generative AI, LLM-based applications, and agentic workflows to deliver measurable business impact within the property and casualty insurance sector.
The candidate should have experience across the full machine learning and AI lifecycle, including data preparation, experimentation, model development, evaluation, production deployment, monitoring, and continuous improvement of advanced data science and AI solutions. They will use robust MLOps practices and AWS technologies to develop scalable, reliable, secure, and high-performing solutions, while working collaboratively with technical teams, business stakeholders, and subject-matter experts. This role offers an opportunity to grow within a collaborative environment, with a focus on technical excellence and delivering meaningful outcomes.
Key Responsibilities:
- Model Development and Optimization:
- Support the design, development, testing, and optimisation of machine learning and AI solutions that address key insurance challenges, including claims analysis, fraud detection, risk assessment, and customer insights.
- Apply a range of traditional AI and machine learning techniques to identify patterns, generate insights, and support data-driven decision-making.
- Develop natural language processing, large language model, and agentic AI solutions that process and interpret unstructured data, generate actionable insights, and enable multi-step workflows that use tools and data sources, coordinate tasks, and support or automate business processes.
- Evaluate and improve the accuracy, reliability, performance, and safety of models and solutions through robust testing, experimentation, and ongoing optimisation.
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Data Engineering and Management:
- Build and maintain pipelines, ensuring data quality and accessibility for modelling purposes.
- Collaborate with data engineers in implementing best practices to support data ingestion, cleaning, and transformation processes.
- Work with AWS and open-source tooling for data storage, processing, and ETL workflows.
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Deployment, MLOps, and Model Monitoring:
- Assist in deploying machine learning models to production environments on AWS, ensuring reliability and performance.
- Contribute to the setup and maintenance of monitoring systems to track model performance, detect data drift, and manage model retraining as necessary.
- Support continuous integration and continuous deployment (CI/CD) pipelines to streamline model updates and minimize disruptions.
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Business Alignment and Stakeholder Collaboration:
- Partner with product teams and stakeholders to understand business requirements and translate them into data science solutions.
- Provide clear, actionable insights based on model outcomes, helping to support decision-making and improve business processes.
- Document data science workflows, model development processes, and performance metrics for transparency and collaboration.
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Research, Innovation, and Continuous Learning:
- Stay updated on advancements in AI, ML, and GenAI, especially those applicable to insurance, to enhance team capabilities and incorporate innovative techniques.
- Participate in proof-of-concept (PoC) projects, contributing to both data science and non-data science initiatives.
- Actively engage in team knowledge-sharing activities to promote a culture of continuous learning.
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General:
- Participate in and complete any training and Continuous Professional Development as relevant to the role and/or as required by the company.
- Adhere to all company policies and procedures including but not limited to Data Protection, Equal Opportunities, and Health & Safety.
This job description is not intended to be exhaustive and may be amended at any time.
Person Specification:
Education:
- Bachelor Honor’s degree (minimum 2:1) or equivalent in computer science, Data Science, Applied Mathematics, Statistics, or a related quantitative field.
Experience:
- Minimum of 4+ years in data science or machine learning roles.
- Proven track record of building and deploying models in production environments.
- Hands-on experience with AWS cloud services, particularly for machine learning and data engineering.
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Technical Skills:
- Proficiency in Python and data science libraries (e.g., scikit-learn, TensorFlow, Keras, Pandas, Seaborn).
- Solid understanding of SQL and experience with NoSQL databases for data manipulation and query optimization.
- Experience developing, fine-tuning, and retraining machine learning models across a range of techniques, including regression, classification, clustering, anomaly detection, deep learning, and ensemble methods.
- Hands-on experience building NLP, LLM, RAG, AI agent, and Agentic AI solutions using relevant models, libraries, frameworks, and standards, including Llama, Hugging Face Transformers, LangChain, LangGraph, LlamaIndex, and MCP to connect AI applications with tools, data sources, and external systems.
- Familiarity with MLOps practices, including version control (Git) and CI/CD processes, for efficient model lifecycle management.
- Experience with containerization (Docker) and an understanding of orchestration tools like Kubernetes.
Soft Skills:
- Strong analytical and problem-solving skills, with the ability to communicate data science concepts to non-technical audiences.
- Collaborative team player, with a proactive approach to cross-functional teamwork.
- Well-organized, detail-oriented, and committed to delivering high-quality work.
- Experience with agile development methodologies, with the ability to adapt quickly in a fast-paced, evolving environment.
Desirable (will be used for further shortlisting purposes):
- Interest in exploring new areas in technology, including JavaScript and web development, for expanded skill-building.
- Understanding of modern data platforms and data engineering practices, including data lakes, data lakehouses, workflow orchestration, and open table formats, with knowledge of tools and technologies such as Dagster, dbt, Apache Iceberg.
- Familiarity with the property and casualty insurance industry, particularly claims processing, underwriting, fraud detection, or risk assessment.
- Relevant AWS certifications, such as AWS Certified AI Practitioner, AWS Certified Machine Learning Engineer – Associate, or AWS Certified Solutions Architect.
- MSc Data Science or related field.
Benefits
- Competitive salary.
- Discretionary Bonus potential.
- 25 days annual leave per annum pro rata plus 10 statutory and public holidays.
- Birthday Leave.
- Pension with total 9% contribution and option for salary sacrifice.
- Health Insurance.
- Life Assurance.
- Income Protection.
- Employee Assistance Programmes (EAPs).
- Hybrid Working with 2 days at home per week.
- Range of additional lifestyle benefits.
Frontline UK is an equal opportunities employer. All appointments are made solely on the basis of merit.
All candidates must be able to demonstrate right to work in the UK.
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