Senior Data Analyst

Orion180•Irving, TX

1d•Onsite

About The Position

This position is for a Senior Data Analyst. The company believes that analytics is not a back-office function or a mere reporting layer, but rather the foundation for identifying risks, growth opportunities, and missed chances before it's too late. This belief drives significant investment in people, platforms, and the integration of analytics into all operations, from underwriting to distribution and customer experience. The goal is to build a data culture where insights lead to action. The role of an analyst is evolving beyond just technical execution, requiring curiosity, ownership, and the ability to navigate ambiguity, frame problems, and guide the business toward better decisions.

Requirements

Bachelor’s degree in Statistics, Data Science, Computer Science, Mathematics, or a related field
Proven experience in data analysis, modeling, and visualization within the insurance or financial services industry.
Proficiency in Python, SQL optimization, statistical modeling, API development, and forecasting techniques.
Hands-on experience with cloud platforms such as AWS, Azure, or GCP and familiarity with MLOps frameworks.
Strong understanding of both data science and actuarial principles.
Excellent analytical, problem-solving, and critical-thinking skills.
Strong communication and collaboration abilities across technical and non-technical teams.
Ability to manage multiple projects in a fast-paced, results-driven environment.

Nice To Haves

Experience or familiarity with semantic data modeling and governed metric layers.
Working within scalable cloud data platforms (e.g., Snowflake, Databricks).
Integrating analytics within broader data engineering workflows.
Exposure to emerging capabilities such as AI-assisted analysis, automated insight generation, and advanced data visualization techniques.

Responsibilities

Develop and maintain reproducible, scalable data pipelines to support advanced modeling and analytics workflows.
Design and implement predictive and time-series models using classical and machine learning methods.
Collaborate with sales, underwriting, claims, and actuarial teams to integrate models into production environments.
Leverage Python, SQL, and statistical analysis to identify key data patterns and multivariate correlations.
Conduct exploratory data analysis and ensure data integrity across structured and unstructured datasets.
Document model assumptions, governance processes, and validation results to maintain compliance with regulatory standards.
Build intuitive dashboards and data visualizations using Power BI that translate complex insights into clear business intelligence.
Communicate findings and recommendations to cross-functional teams, including leadership and technical partners.
Stay current with industry trends and emerging data science tools to continuously improve analytical capabilities.