Senior Insights Analyst - Data Analytics

Assurant•Atlanta, GA

2d•$88,000 - $147,000

About The Position

The Senior Insights Analyst is a hands-on individual contributor who turns complex data into clear, actionable recommendations for senior leaders, internal business partners, and external client audiences. The role independently handles the full analytics lifecycle, shapes ambiguous business questions, mentors fellow analysts, and delivers trusted insights that influence decisions. The analyst leads high-visibility analytical projects and insight deliverables supporting business performance, client relationships, operational strategy, and executive decision-making. The work combines hands-on analysis and modeling with project leadership, peer mentoring, and modernization of reporting and insight capabilities. The role also supports data strategy and governance, advances the use of AI and machine learning, and develops advanced analytics products to improve customer experience, growth, competitive advantage, and decision-making. Success includes independently delivering accurate, reproducible, clearly communicated analysis; leading projects from scoping through delivery; presenting recommendations to senior leaders or clients; identifying opportunities to automate or govern reporting; mentoring teammates; and delivering adopted predictive or advanced analytics products. Travel potential is up to 10%.

Requirements

Master’s degree in Business Analytics, Statistics, Economics, Applied Mathematics, Computer Science, Information Management, or a related quantitative field; equivalent work experience may be considered.
At least 7 years of experience in business analysis, research, statistics, applied mathematics, data management, business intelligence, or a related field.
At least 7 years of experience with data science tools such as R, Python, SQL, Advanced Excel, and Power BI, and with relational database software.
At least 7 years of data analysis experience that includes translating insights into recommendations.
At least 5 years of experience leading analytical projects.
Experience performing statistical analyses, including predictive modeling, time series analysis, exploratory data analysis, segmentation and cluster analysis, and retention analysis.
Advanced SQL skills, including complex joins, window functions, CTEs, data validation, and working directly with enterprise data warehouses.
Strong Power BI experience, including data modeling, DAX, semantic model development, and governed self-service analytics.
Working knowledge of cloud technologies such as Azure (Databricks, Azure ML, Cognitive Services) or Microsoft Fabric.
Advanced Excel skills and comfort using modern analytics, automation, and AI-assisted tools to improve productivity and documentation.
Strong written, verbal, and interpersonal communication skills, with the ability to communicate effectively at all organizational levels.
Strong data storytelling skills, including distilling complex information into understandable ideas, business implications, and recommended actions.
Strong analytical and research skills, an innovative approach to problem solving, and a track record demonstrating it.
Ability to work independently on all project types.

Nice To Haves

Degree in statistics, applied mathematics, operations research, economics, engineering, computer science, or a related quantitative field.
Experience working in the insurance industry.
Experience with Databricks, Azure, Python, R, Copilot, or Claude.
Experience modernizing legacy reporting, consolidating dashboards, defining KPI frameworks, and improving semantic models.
Hands-on use of AI-assisted coding, documentation, or analytics tools to accelerate analysis and responsibly automate recurring work.
Track record of mentoring peers and fostering curiosity, accountability, inclusion, and continuous improvement.

Responsibilities

Produce clear presentations, visualizations, and dashboards that identify business opportunities and provide actionable recommendations.
Use tools including Azure, Python, SQL, Excel, and Power BI to transform data into insights and quantify opportunities.
Build studies through proactive data analysis and research to support decision-making.
Translate business challenges into predictive modeling opportunities and collaborate with stakeholders to define forward-looking questions.
Build and validate ad-hoc predictive models using techniques such as regression, time series forecasting, and classification.
Lead analytical projects, help develop project plans, conduct analysis and modeling, test hypotheses, present complex information clearly, and identify next steps and future opportunities.
Mentor team members in technical proficiency, code reviews, and business acumen.
Collaborate with team members to prioritize multi-resource requests and complete projects thoroughly and on schedule.
Participate in and help drive data modeling and governance best practices across Power BI, Microsoft Fabric, and related analytics environments.
Engage internal and external teams proactively to identify analytical needs.
Advance company-wide understanding and implementation of AI and machine learning, and improve team practices using lessons from existing implementations.
Present compelling data-based business cases to optimize investments and operations.
Communicate with and educate technical and non-technical employees about analytics and data-driven decision-making.
Work cross-functionally with business owners to develop advanced analytics products that improve customer experience, support growth, create competitive advantage, and improve decision-making.