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 Senior 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
Note on Seniority:
While this position is advertised as Senior Data Scientist, we recognize that exceptional candidates may bring experience and leadership qualities suitable for a Lead or Principal Data Scientist role. The final level and title will be determined based on the candidate's skills, experience, and potential impact.
The Role
We are looking for a Senior Data Scientist with deep experience in machine learning, natural language processing (NLP), and large language models (LLMs). The ideal candidate will lead the design, development, and deployment of machine learning models and solutions, applying both traditional and advanced methods to drive measurable impact within the property and casualty insurance sector. This role requires expertise across the entire ML lifecycle, from data preprocessing to production deployment and monitoring, using robust MLOps and AWS practices to deliver scalable, high-performance solutions.
Key Responsibilities:
Model Development and Optimization:
* Design, build, and optimize machine learning models to solve a variety of business challenges in insurance, including claims analysis, fraud detection, risk assessment, and customer service.
* Utilize diverse machine learning techniques, such as supervised and unsupervised learning, anomaly detection, time series analysis, and predictive modelling.
* Develop, fine-tune, and implement NLP models and generative AI (including Retrieval-Augmented Generation (RAG)) for applications like automated document processing, customer interaction, and risk scoring.
* Evaluate and enhance model performance through rigorous testing, validation, and tuning to ensure reliability and accuracy across business applications.
Data Engineering and Management:
* Build scalable data pipelines for structured and unstructured data, optimizing data ingestion, cleaning, and transformation processes to support model development.
* Collaborate with data engineers to ensure seamless data integration, storage, and accessibility, implementing best practices for data management and governance.
* Leverage AWS and open-source data engineering tools to create efficient ETL workflows and enable large-scale data processing and real-time analytics.
Deployment, MLOps, and Model Monitoring:
* Collaborate closely with MLOps teams to deploy machine learning models into production environments on AWS, ensuring reliability, scalability, and fault tolerance.
* Implement and maintain robust monitoring systems for ML models in production to track performance, detect data drift, and schedule model retraining as needed.
* Design and establish continuous integration/continuous deployment (CI/CD) pipelines to streamline model updates and minimize downtime.
Business Alignment and Stakeholder Collaboration:
* Partner with cross-functional teams, including product managers, business analysts, c-suite executives to define technical requirements that align with business goals and customer needs.
* Translate complex data science concepts into actionable insights for stakeholders, supporting decision-making with clear, data-driven recommendations.
* Develop comprehensive documentation of modelling processes, data pipelines, and model performance metrics for transparency and knowledge sharing across the organization.
Research, Innovation, and Continuous Learning:
* Stay up to date on AI, ML, and NLP advancements, particularly those relevant to the insurance sector, integrating new techniques and tools as appropriate.
* Lead proof-of-concept (PoC) projects for both data science and non-data science applications, to showcase potential advancements for business objectives.
* Drive continuous learning within the team, sharing best practices and encouraging exploration of emerging technologies and methodologies.
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 5+ years in data science or machine learning roles.
* Proven track record of building and deploying machine learning models in production environments, with specific experience in the insurance sector a plus.
* Extensive experience with AWS cloud services and open-source technologies, particularly for machine learning and data engineering.
Technical Skills:
* Proficient in Python and machine learning libraries such as scikit-learn, TensorFlow, Keras and Pandas for model development.
* Strong knowledge of SQL and NoSQL databases, data manipulation, and query optimization.
* Experience with diverse machine learning techniques, including regression, classification, clustering, anomaly detection, deep learning and ensemble methods.
* Hands-on experience with NLP techniques (e.g., tokenization, embeddings, sentiment analysis, entity recognition) and LLMs and frameworks like Llama and LangChain.
* Solid understanding of MLOps practices, version control (Git), and CI/CD pipelines to streamline model deployment and management.
* Familiarity with containerization (Docker) and orchestration tools (Kubernetes) to manage and scale AI applications in cloud environments.
Soft Skills:
* Strong analytical and problem-solving skills with the ability to communicate complex technical ideas to non-technical stakeholders.
* Proactive and collaborative team player, with the ability to lead projects across diverse teams.
* Excellent organizational skills, with a keen eye for detail and a commitment to quality and accuracy.
* 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):
* A passion for continuous learning and skill development in areas beyond core data science, such as JavaScript and web development.
* Familiarity with the insurance industry, especially in areas of underwriting, claims automation, or fraud detection.
* AWS certifications such as AI Practitioner Certification, Machine Learning Engineer, Solutions Architect.
Benefits:
* Competitive salary.
* Discretionary Bonus potential.
* 25 days annual leave per annum pro rata plus 10 statutory and public holidays and 1 additional day's Birthday Leave.
* Pension with total 9% contribution and option for salary sacrifice.
* Health Insurance.
* Life Assurance.
* Income Protection.
* Employee Assistance Programme (EAP).
* Hybrid Working with 2 days at home per week.
* Onsite parking.
* Range of additional CPD and lifestyle benefits.
Candidates should submit a CV for the role to
Closing Date:
Friday 10th October pm.
FRONTLINE UK IS AN EQUAL OPPORTUNITIES EMPLOYER. ALL APPOINTMENTS ARE MADE SOLELY ON THE BASIS OF MERIT.