Data Scientist

Data Scientist (Mid-Level) – Centre of Excellence (CoE)

Description

Are you ready to help shape the next wave of AI-driven transformation at LII? Join our Data Science Centre of Excellence (CoE) as a Mid-Level Data Scientist, where you will take a leading role in translating complex business problems into scalable, AI-powered solutions.

In this role, you will not only contribute to experimentation and model development but also own end-to-end solution delivery—from ideation and prototyping to deployment and optimization. You will work on cutting-edge AI initiatives including Generative AI (GenAI), leveraging LLMs, prompt engineering, and advanced ML techniques to drive business impact.

You will collaborate with cross-functional teams across LII, GRS, and Liberty Mutual, guiding projects, mentoring junior team members, and helping establish best practices across the CoE. This is a fast-paced, high-impact environment where adaptability, technical depth, and business orientation are critical.

Responsibilities

• Lead design and execution of data science solutions for high-priority business problems, ensuring measurable business impact

• Own end-to-end lifecycle of models including data exploration, feature engineering, model development, validation, deployment, and monitoring

• Develop and deploy machine learning and GenAI solutions into production environments in collaboration with engineering and IT teams

• Work with Large Language Models (LLMs) and contribute to prompt engineering, prompt optimization, and evaluation frameworks

• Design and run experiments with GenAI solutions (e.g., document processing, summarization, conversational AI, OCR enhancement)

• Optimize prompts and model outputs for accuracy, latency, and cost efficiency in business use cases

• Collaborate with stakeholders to translate business needs into technical solutions and ensure alignment with strategic priorities

• Mentor junior data scientists and contribute to capability building within the CoE

• Help define and enforce best practices in MLOps, model governance, and responsible AI

• Manage and prioritize project backlog, balancing innovation initiatives with production delivery

• Analyse and communicate insights, ensuring clear articulation of ROI and business value

• Stay up to date with emerging trends in AI/ML, GenAI, and MLOps, and bring innovative ideas into the organization

Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or related field

• 3–5 years of hands-on experience in data science, machine learning, or applied AI

• Strong programming experience in Python (preferred) or R, and familiarity with ML frameworks (scikit-learn, TensorFlow, PyTorch)

• Experience working with Generative AI / LLMs, including APIs (e.g., OpenAI, Azure OpenAI, or similar ecosystems)

• Proven experience in prompt engineering and prompt optimization, with a strong understanding of evaluation metrics and trade-offs

• Experience in deploying ML models to production, including knowledge of APIs, cloud platforms (Azure/AWS/GCP), and MLOps practices

• Familiarity with model monitoring, versioning, and lifecycle management

• Strong analytical and problem-solving skills with the ability to translate business problems into scalable solutions

• Experience handling end-to-end data science projects, including stakeholder engagement and delivery ownership

• Ability to communicate technical concepts clearly to non-technical stakeholders

• Experience in insurance or financial services is a plus

• Exposure to document AI, OCR, or vision-language models is a strong advantage