Senior Data Analyst

paretocaptiveservicesllc; United States; Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Hybrid work environment

Tuition reimbursement

Professional development allowance

Transportation or parking support

Job summary

Pareto Captive Services LLC is seeking a senior analytics professional to bridge business intelligence and data science in healthcare. You will turn complex healthcare data into durable analyses and actionable recommendations for stakeholders, prioritizing reusable datasets and maintainable solutions.

This is not focused on production ML or people management. You will collaborate with analysts, data scientists and business partners on ambiguous questions, building transparent methods, clear

Qualifications

• 5–8+ years in healthcare analytics with US health insurance knowledge.
• Hands-on experience with administrative healthcare data (medical and pharmacy claims).
• Strong quantitative and statistical foundations for real-world data.
• Strong SQL skills for complex queries; proficient in Python for analysis.
• Proficient data visualization with Tableau and data quality validation.
• Bachelor’s degree in a quantitative field; master’s preferred.

Responsibilities

• Translate business priorities into analytical analyses from question to delivery.
• Develop and refine methods for complex questions with reusable datasets.
• Work with large medical/pharmacy claims data; build and optimize SQL queries.
• Explain findings with clear visuals and summaries for all audiences; turn into recommendations.
• Document methods, assumptions, limitations for transparency and repeatability.
• Coordinate with analytics teammates to align data quality and methods.

Skills

SQL

Python

Data visualization

Statistics

Healthcare analytics

Education

Bachelor’s degree in quantitative field

Master’s degree or equivalent

Tools

Tableau

SQL

Job description

Role overview

This senior individual-contributor role sits between business intelligence and data science, turning complex healthcare data into durable analysis and decisions. You will work with analysts, data scientists and stakeholders on ambiguous questions, with an emphasis on reliable methods, reusable datasets and solutions that can be maintained and used across the organization. The position does not focus on production machine learning or people management.

Responsibilities

• Translate business priorities into analytical approaches and lead or contribute to analyses from question definition through delivery.


• Develop, test and refine methods for complex questions, considering how results can be sustained and reused.


• Work with large, messy medical and pharmacy claims datasets; build, optimize and validate SQL queries and analytical datasets.


• Explain findings through clear visualizations and summaries for technical and non-technical audiences, and turn analysis into recommendations.


• Document methods, assumptions and limitations so analyses are transparent and repeatable.


• Coordinate with analytics teammates to align definitions, methods and data quality, and identify opportunities where analysis can improve outcomes.

Requirements

• 5–8 or more years in healthcare analytics, preferably in health benefits or insurance, with a sound understanding of the US health insurance system.


• Extensive hands‑on experience with administrative healthcare data, including medical and pharmacy claims.


• Strong quantitative and statistical foundations, and judgment in selecting appropriate methods for real-world data.


• Strong SQL skills for complex analytical queries, alongside substantial experience using Python for analysis and data wrangling.


• Advanced proficiency with data visualization tools such as Tableau, plus experience cleaning, validating and exploring large datasets.


• Familiarity with descriptive statistics, cohort and trend analysis, risk assessment and causal reasoning; a quantitative bachelor’s degree or equivalent experience. A master’s degree or equivalent experience is preferred.

Nice to have

• Deep Python knowledge; experience with Salesforce, vendor-reported utilization and savings data, or stop‑loss insurance data.


• Familiarity with healthcare underwriting or actuarial risk assessment, and AWS data services such as S3, Lambda, Glue, SageMaker or EMR.

Benefits and work setup

• Hybrid work environment, flexible paid time off and employer contribution to a retirement plan.


• Medical, dental and vision coverage, tuition reimbursement, a professional development allowance, and transportation or parking support.

Candidates must be authorized to work in the United States without employment visa sponsorship.