Senior Data Analyst at Nationsbenefits, Remote

Senior Data Analyst at Nationsbenefits, remote. Est. up to $130k. Apply with swipeandhired.

NationsBenefits is recognized as one of the fastest-growing companies in America and a Healthcare Fintech provider of supplemental benefits, flex cards, and member engagement solutions. We partner with managed care organizations to provide innovative healthcare solutions that drive growth, improve outcomes, reduce costs, and bring value to their members.

Through our comprehensive suite of innovative supplemental benefits, fintech payment platforms, and member engagement solutions, we help health plans deliver high-quality benefits to their members that address the social determinants of health and improve member health outcomes and satisfaction.

Our compliance-focused infrastructure, proprietary technology systems, and premier service delivery model allow our health plan partners to deliver high-quality, value-based care to millions of members.

We offer a fulfilling work environment that attracts top talent and encourages all associates to contribute to delivering premier service to internal and external customers alike. Our goal is to transform the healthcare industry for the better! We provide career advancement opportunities from within the organization across multiple locations in the US, South America, and India.

Role Overview

We are seeking an experienced Senior Data Analyst to deliver actionable insights that improve product performance, program outcomes, operational effectiveness, and customer decision-making.

This role will partner closely with Product, Operations, Client Success, and other business teams to understand how our products and programs are performing, identify opportunities for improvement, and develop the analytical frameworks needed to measure success.

The ideal candidate combines strong SQL and analytical skills with business judgment, curiosity, and the ability to translate complex data into clear recommendations. This role will work extensively within Databricks to analyze large and complex datasets across our products, members, clients, and programs.

Key Responsibilities

Product & Program Analytics

• Partner with Product and business leaders to define KPIs and measurement frameworks for products, programs, and strategic initiatives.

• Analyze product performance, utilization, adoption, engagement, financial performance, and member behavior.

• Develop analytical frameworks that help teams understand what happened, why it happened, and what actions should be taken next.

• Conduct deep-dive analyses to identify trends, opportunities, anomalies, and drivers of business performance.

• Evaluate new product capabilities, program changes, and business initiatives using appropriate analytical techniques.

• Develop ongoing measurement approaches that allow teams to track performance over time.

Data Analysis & Insights

• Write advanced SQL within Databricks to analyze large, complex datasets across multiple business domains.

• Combine data from multiple sources to develop comprehensive views of customers, members, products, and programs.

• Perform exploratory analysis, segmentation, cohort analysis, trend analysis, and root-cause investigation.

• Identify meaningful relationships and patterns within data and translate findings into business implications.

• Develop clear recommendations based on analytical findings rather than simply reporting results.

• Respond to complex analytical questions and ambiguous business problems with structured, data-driven approaches.

Metrics & Analytical Foundations

• Partner with Analytics Engineering and business stakeholders to define consistent business metrics, KPIs, and analytical definitions.

• Help establish standardized measurement approaches across products and programs.

• Identify data quality, availability, or modeling issues that limit analysis and work with data engineering and analytics engineering teams to resolve them.

• Validate analytical datasets and ensure metrics accurately represent underlying business processes.

• Contribute business and analytical requirements to the development of reusable Gold-layer datasets and analytical data products.

Reporting & Decision Support

• Develop recurring analytical views and reporting that allow product and business teams to monitor performance.

• Support external customer reporting and analysis by providing accurate, explainable, and consistent metrics.

• Move recurring analytical needs toward standardized and reusable solutions rather than repeated one-off analysis.

• Translate complex analytical findings into concise presentations, visualizations, and recommendations for technical and non- technical audiences.

• Provide analytical support for business reviews, product reviews, client discussions, and strategic planning.

Business Partnership

• Develop deep expertise in assigned products, programs, and business domains.

• Serve as the analytical partner to Product Managers and business leaders, helping them define questions and determine how data can inform decisions.

• Proactively identify analytical opportunities rather than relying solely on incoming requests.

• Challenge assumptions and help stakeholders distinguish between symptoms, underlying drivers, and actionable opportunities.

• Communicate analytical findings clearly, including limitations, assumptions, and areas of uncertainty.

Qualifications

• 5+ years of experience in data analytics, product analytics, business analytics, or a related discipline.

• Advanced SQL skills and experience working with large, complex datasets.

• Strong experience using Databricks or comparable modern cloud data platforms.

• Demonstrated experience supporting product, program, or business performance analytics.

• Strong understanding of analytical techniques including segmentation, cohort analysis, trend analysis, variance analysis, and root-cause analysis.

• Experience developing KPIs, metrics, and measurement frameworks.

• Ability to translate ambiguous business questions into structured analytical approaches.

• Strong data validation and problem-solving skills.

• Experience communicating analytical findings and recommendations to business and product stakeholders.

• Ability to work effectively across Product, Engineering, Operations, and business teams.

Ideal Profile

This role is best suited for someone who sees analytics as more than producing reports or answering ad hoc questions.

The successful candidate will develop deep knowledge of the products and programs they support, understand the business processes behind the data, and use that knowledge to identify opportunities and influence decisions.

They should be equally comfortable writing complex SQL in Databricks, investigating unexpected changes in product performance, defining a new KPI with a Product Manager, and presenting a clear recommendation to business leadership.

Success in this role means becoming a trusted analytical owner for a product or program—not simply a provider of data.