Sr Data Analyst

BP&C•New York City, NY

14h•Onsite

About The Position

The Sr Data Analyst partners with stakeholders across P&C Operations (Underwriting, Product, Actuarial, Claims, and Marketing) to deliver advanced analytical insights that inform business strategy and operational decision-making. This role’s responsibility includes performing data analysis (e.g., conceptualization, mining/modeling, and presentation of data) and developing methods to efficiently capture, manage, and analyze data. The position serves as a trusted partner to business leaders by translating complex data into clear, actionable insights and identifying opportunities to improve processes and outcomes. This is a 100% in-office position. Candidates must be able to work on-site at a designated company office during standard business hours.

Requirements

Four to six years of relevant work experience
Bachelor’s degree in mathematics, computer science, data science, data analytics, or a related field. Equivalent work experience in a business or technical environment will be considered in lieu of a bachelor’s degree.
Proficient in Python/PySpark, SQL (CTE, window functions) and Power BI using graphs, charts, and map features.
Experience in data quality control/governance, data mining, and modeling
Working knowledge of emerging analytics technology (e.g., Agentic AI/ML concepts)
Strong soft skills with clear, effective oral and written communication.

Nice To Haves

Experience in Microsoft Fabric, Snowflake Ecosystem, and Visual Studio Code
Strong understanding of Property & Casualty insurance data concepts and operational workflows is preferred.

Responsibilities

Partners with stakeholders to define business problems, translate data needs into analytical solutions, and ensure alignment between business objectives and data outputs.
Develops and maintains methods to distribute management information, as appropriate, throughout P&C Operations using tools, standards, and platforms in use at the time with minimal guidance.
Designs, develops, and maintains dashboards (Power BI), reports, and data products for use throughout P&C Operations using the tools, standards, and platforms in use at the time with minimal guidance.
Develops and optimizes SQL queries, Python/PySpark scripts, and data pipelines to extract, transform, and validate data for analysis and reporting.
Independently leads analytics initiatives, managing priorities, timelines, and deliverables from intake through deployment.
Responds to support questions promptly, courteously, and accurately, with an analysis of the results and any issues or changes made with minimal guidance.
Synthesizes analytical findings into clear insights and recommendations, tailoring communication for both technical and non-technical audiences.
Ensure enterprise reporting and analytics adhere to defined data governance standards, business rules, and data quality expectations.
Validates data accuracy and completeness across source systems and downstream reporting layers, identifying trends, anomalies, and data quality issues.
Performs quality assurance checks to validate completeness and accuracy of data and/or deliverables for release with minimal guidance.
Supports recurring operational data needs (e.g., month‑end, quarter‑end, and ongoing production reporting cycles) by ensuring timely, accurate delivery of analytics and reports.
Identifies trends, patterns, and opportunities within data to support process improvements and strategic initiatives.
Document, update, and utilize the policies, procedures, and processes used throughout P&C Operations.
Mentor junior analysts by reviewing policies, procedures, and processes and validating the queries/code, reports, and dashboards for accuracy and quality.
Proactively identify opportunities with the appropriate stakeholders to remedy the errors timely with minimal guidance.
Ensures that the data produced remains secure, respecting corporate privacy and security procedures.
Assists with training for stakeholders in areas such as proper data usage, SQL, or Power BI.
Collaborate with data engineering and platform teams to ensure alignment between analytics solutions and enterprise data platforms (e.g., cloud data warehouses, semantic models, and BI environments).