Insurance Data Scientist

Summary/Job Purpose:

Data and analytics are at the heart of decision making at MSIG USA – a data-driven specialty insurance provider in the US. We are seeking a highly analytical and innovative Insurance Data Scientist to join our Insurance Analytics team to help drive profitable growth in new and existing markets. This role involves designing and implementing advanced algorithms to extract actionable insights from large and complex datasets, applying statistical and machine learning techniques to solve business problems, and collaborating across departments (Pricing, Underwriting, Claims, Actuarial, etc.) to enhance decision-making. The ideal candidate will possess balanced tactical and strategic thinking, problem-solving skills, and the ability to communicate technical findings to non-technical stakeholders. A passion for data-driven decision making in the insurance domain is essential.

Essential Functions:

• Perform ad-hoc and recurring analyses across all insurance business units (e.g., pricing, underwriting, claims, operations, etc.) and lines of business. Extract insights from structured and unstructured data sources, including text.
• Develop end-to-end data science and analytics solutions (for all business units), including data preparation, model development, testing, documentation, implementation, monitoring, and iteration.
• Identify required technology and tools to support analysis and solutions, collaborating with other teams to implement these tools.
• Develop and implement data pipelines to support analytical needs and tools. Augement existing datasets with derived data and external information.
• Design visualizations and dashboards to support insight sharing and enable real-time performance monitoring. Implement these solutions utilizing dashboarding tools and custom web applications.
• Collaborate cross-functionally with IT, Data, Claims, Underwriting, Actuarial, Finance, and Leadership to identify and solve high-impact problems. Work with these stakeholders to define the data science and analytics needs and become a trusted business partner by delivering on these requirements.
• Contribute to the prioritization and roadmapping of data and analytics initiatives.
• Communicate findings effectively to both technical and non-technical audiences.
• Continuously seek opportunities to learn new skills and techniques, and actively share knowledge with peers.

Supervisory Responsibilities:

This position has no supervisory responsibilities.

Qualifications: To perform this job successfully, an individual must be able to perform each essential duty. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• Technical – Solid statistical, machine learning and data science skills, utilizing a variety of tools
• Tactical thinking – Ability to execute on short-term business needs
• Strategic thinking – Ability to visualize long-range solutions to business goals
• Innovation - Displays original thinking and creativity
• Problem Solving - Identifies root causes and resolves problems in a timely manner
• Teamwork - Balances team and individual responsibilities
• Judgment - Makes timely and sound decisions
• Planning/Organizing - Prioritizes and plans work activities
• Quality - Demonstrates and enforces accuracy and thoroughness
• Initiative - Volunteers readily; Undertakes self-development activities; Seeks increased responsibilities

Education and Experience Required:

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related field
• Minimum of 5 years of relevant experience in data science and analytics, including machine learning
• Strong proficiency in Python or R for statistical analysis, model development, and application deployment
• Experience setting up and using various different data science tools (e.g. Airflow, Jupyter Notebooks, H20, Spark, etc.)
• Experience with dashboarding tools (e.g. Tableau, Power BI, etc.)
• Advanced SQL skills for data extraction, transformation, and manipulation
• Proven track record of end-to-end development of machine learning models
• Experience with data visualization tools such as Tableau or Power BI
• Excellent problem-solving and critical thinking abilities
• Strong communication skills with the ability to convey technical concepts to non-technical stakeholders

Preferred Qualifications

• Experience in data science and analytics for commercial insurance, across all ines of business
• Experience using a range of different coding languages
• Experience working with unstructured data, including text, images, and video
• Familiarity with cloud computing platforms such as AWS or Azure