Lead Applied Scientist

Lead Applied Scientist
New York, NY - hybrid 3 days onsite
Full time - W-2 only

In addition, you will be offered competitive target incentive compensation, with awards based on overall corporate and individual performance. On top of this, you will be eligible for a comprehensive and competitive benefits package which includes medical plans for you and your family, health and wellness programs, retirement plans, tuition reimbursement, paid vacation, and much more.


Manager's call notes:

• Doesn't need to come from insurance although it would be nice
• True technically brilliant person. They will have signoff authority on proposed changes and implementations
• Looking at code and making sure everything is good to go
• Doer and a thought leader
• PYTHON, panda, Azure, databricks, computer engineering background

How does this role contribute to our collective success?

Data and analytics are of critical importance for the company. Simply put, we want to turn data into information, that can be used to:

• Enable decisions to be made with confidence, based on information not just intuition.
• Be more proactive, using information to identify new opportunities, and getting to them before our competitors.
• Realize cost savings, finding ways to make processes more efficient, enabling our people to focus on using their skills to further add business value.

This team is working to transform the way in which we do business and to enable us to effectively leverage the latest AI advancements to our competitive advantage.
The Data Science & AI Delivery Lead is a key leadership role within this team, acting as the deputy to the Head of Data Science & AI Delivery and ensuring the smooth day-to-day running of AI delivery operations.
The Data Science & AI Delivery Lead is the technical delivery leader for AI, machine learning, and advanced analytics solutions. This role owns technical execution, engineering standards, solution architecture, deployment quality, and production delivery of AI capabilities. This role focuses on how solutions are designed, built, deployed, and scaled.

What will you do in this role?

The Data Science & AI Delivery Lead acts as the right hand to the Head of Data Science & AI Delivery, taking ownership of the day-to-day execution and coordination of data science and AI delivery across strategic projects and standalone use cases. You will play a hands-on leadership role
- driving technical delivery, managing workstreams, and stepping in for the Head of when required.

This is not a purely managerial role. You will be expected to work directly in the codebase, review and shape technical designs, and maintain deep fluency with the tools and techniques the team uses daily. Working closely with the Head of, you will ensure projects are delivered to a high standard, on time, and with strong stakeholder engagement.

In this role you will be responsible for:
Day-to-Day Delivery Leadership:

• Own the operational running of AI delivery workstreams, ensuring the team is focused, unblocked, and delivering against priorities. Engineering standards, patterns, reusable frameworks, and delivery best practices.
• Design reviews, implementation approaches, and production readiness reviews. Establish execution across all AI delivery workstreams. Lead architectural decisions, technical Act as the primary point of escalation when the Head of is unavailable. Own technical
• Project Management: Own technical delivery accountability from concept through production.
• Ensure solutions meet security, governance, scalability, explainability, and operational support standards.
• Technical Oversight & Contribution: Provide technical guidance on solution design, model selection, and architecture decisions, ensuring the team is taking the right approach for each use case.
• Review code and technical outputs to maintain quality standards and contribute hands-on to Python-based development when needed, particularly during critical delivery phases or proof-of-concept work.
• Support the design and delivery of Generative AI solutions, including RAG architectures, prompt engineering, and integration with Azure AI services (e.g., Azure OpenAI, Azure AI Search).
• Ensure robust MLOps practices are followed, including model versioning, testing, deployment pipelines, and monitoring of deployed solutions for performance and drift.
• Champion engineering best practices across the team, including code review standards, documentation, version control (Git), and a clear separation between experimentation and production-ready code.
• Technical Strategy & Architecture: Own AI solution architecture and technical design standards.
• Define engineering approaches for LLM applications, agentic systems, machine learning solutions, and AI platforms.
• Lead evaluation of emerging AI technologies and determine appropriate adoption.
• Establish standards for MLOps, AI observability, model lifecycle management, and responsible AI implementation.
• Collaboration: Work closely with our Business Technology Solutions for solution architecture and delivery, and with the Program Office for planning deliveries, providing timelines, cost estimates, and status updates. Partner with Data Engineering to ensure data pipelines and Lakehouse structures support AI delivery needs.
• Team Development: Support the Head of Data Science & AI Delivery in leading and developing a growing team of Data Scientists and AI Engineers, fostering a culture of excellence, collaboration, and continuous learning.
• Mentor and coach team members through hands-on pairing, structured code reviews, and knowledge-sharing sessions on emerging techniques and tools.
• Provide hands-on coaching through architecture reviews, code reviews, pair programming, model reviews, and technical mentoring.
• Maintain technical credibility as a practitioner leader who remains actively involved in delivery.
• Resource & Capacity Planning: Support the Head of in tracking the project pipeline, estimating costs (including cloud computing and API consumption), and managing resource allocation to ensure the team is effectively deployed against priorities.
• Technology Vision: Stay current with the rapidly evolving AI landscape, including new foundation models, open-source frameworks, vector databases, orchestration tools (e.g., LangChain, Semantic Kernel), and evaluation methodologies. Bring new ideas to the team and lead proof-of-concept development to assess feasibility and value.
• Deputising: Represent the Head of Data Science & AI Delivery in meetings, steering groups, and stakeholder forums as required, ensuring continuity of leadership and communication.

You may also be required to take on additional duties, responsibilities, and activities appropriate to the nature of this role. This role reports to the Head of Data Science & AI Delivery.

About You:
We encourage you to bring your own experience and expertise to the table so, while there are some qualifications and experiences we need you to have, we are open to discussing how your individual knowledge might lend itself to fulfilling this role and help us achieve our goals.

What you need to have:

• Demonstrable experience delivering AI/ML solutions in a professional environment, with a track record of taking projects from concept through to production.
• Strong technical knowledge, including expert-level Python proficiency and experience with core data science and ML libraries (e.g., scikit-learn, pandas, PyTorch or TensorFlow).
• Practical experience with Databricks, including MLflow for experiment tracking and model management, and Spark-based data processing.
• prompt engineering, RAG patterns, and vector search.
• Familiarity with Generative AI concepts and tooling, including working with LLMs,
• A solid understanding of MLOps principles, including CI/CD for models, automated testing, and monitoring of deployed solutions.
• Cloud platform experience, preferably Azure, including services such as Azure OpenAI, Azure Machine Learning, or Azure AI Search.
• Experience managing or leading technical delivery teams while remaining hands-on, with a track record of fostering a positive, high-performing team culture.
• Excellent communication skills and the ability to translate complex technical concepts for business stakeholders.
• Strong project management skills, including resource estimation, progress tracking, and meeting deadlines in a fast-paced, multi-priority environment.
• A proactive, problem-solving mindset with the ability to operate independently and step up into a leadership vacuum when needed.

What we prefer you have:

• Experience with advanced NLP techniques beyond prompt engineering, including fine-tuning and evaluation frameworks for generative models.
• claims, or actuarial data.
• Experience working in the (re)insurance industry, with an understanding of underwriting, fairness testing.
• Knowledge of responsible AI practices, including bias detection, explainability, and Role Factors:

In this role, you will typically be required to:

• Attend your local office at least three (3) days per week to meet and build relationships with colleagues and the wider business.
• Engage in company activities to grow your network and build a strong team culture.