Lead Property & Casualty Data Scientist

BP&C•Houston, TX

7d•Onsite

About The Position

Company Shared Services Argo and Farm Family are specialty property and casualty insurance brands whose underwriting companies are wholly-owned subsidaries of Clearbrook Holdings Inc. Argo and Farm Family partner with agents and brokers to provide insurance solutions that enable businesses to manage risks with confidence.

Requirements

Master or foreign equivalent in Computer Information Systems, Computer Science, Mathematics, Statistics, Data Science, Data Analytics or related field.
5 years experience as Data Scientist, Senior Analyst, Software Engineer or related occupation.
Must have at least 1 year of prior work experience in each of the following: Programming languages SQL, Spark, Python, R, and frameworks in the development, articulation, and implementation of coding practices for a team.
Working with large datasets using big data technologies and script.
Formulating, approaching, analysing, and solving analytical problems using a quantitative, scientific approach.
Managing data to scale using data summarization, query and analysis software and tools.
Developing and managing projects and leading interdisciplinary teams to accomplish project goals.
Analytics and machine learning solution design, deployment, and performance monitoring, including models using time series forecasting, propensity modeling, clustering, similarity algorithms, and behavioral prediction techniques, delivered in an Agile environment.

Responsibilities

Own the design and delivery of advanced data science solutions supporting Property & Casualty business objectives.
Anticipate business needs and apply advanced statistical modeling, machine learning, and big data techniques to analyze complex datasets and generate actionable insights and competitive advantage.
Serve as the primary analytics lead for translating business challenges into effective modeling and technical solutions.
Be accountable for leading data science initiatives across the full model lifecycle, including data exploration, model development, validation, implementation, and monitoring.
Define and maintain modeling standards, methodologies, and best practices to ensure quality, consistency, scalability, and reuse.
Provide technical leadership, mentorship, and direction to data scientists and analysts.
Incorporate industry trends, competitor intelligence, and emerging analytics techniques into model development and enhancement.
Partner with business, analytics, and technology teams to deliver data driven solutions aligned with organizational goals and strategic priorities.