Pro90 ProblemsSQL + Python
Health Claims SQL & Python Interview Questions
Healthcare analytics teams process insurance claims, clinical outcomes, and cost data for fraud detection, care utilization measurement, and compliance reporting. These SQL and Python challenges are modeled after work at UnitedHealth, CVS Health, Cigna, Humana, Elevance Health, Kaiser Permanente, BCBS, Centene, Molina Healthcare, and more. Master claims processing analysis, member risk scoring, cost benchmarking, and regulatory reporting.
Companies working in Health Claims
These practice problems are modeled after the kind of data and analytics challenges teams in this industry typically face.
Company names and logos are trademarks of their respective owners, used here only to describe the kind of data these companies work with. Let's Data Science is not affiliated with, endorsed by, or sponsored by any company shown. Practice problems are original works and are not real interview questions from these companies. Rights & takedowns.
Difficulty Distribution
Easy
16
18% of problems
Medium
37
41% of problems
Hard
33
37% of problems
Expert
4
4% of problems
What You'll Practice
Claims processing analysis
Fraud detection patterns
Care utilization metrics
Provider performance
Member retention
Cost trend analysis
Diagnosis code grouping
Risk score modeling
Topics Covered
SQL· 9
aggregationbasic queries filteringcleaning transformdate timejoinsscenario sqlset operationssubqueries cteswindow functions
Python· 12
eda statisticsfeature engineeringpandas aggregationpandas applypandas basicspandas cleaningpandas datetimepandas filteringpandas mergingpandas reshapingpandas scenariopandas window
All Problems90 total
01
Active PPO Plans With Prescription CoveragePro
SQLEasy02Approved High-Value ClaimsPro
SQLEasy03Surgical Procedures Requiring Prior AuthPro
SQLEasy04Active Providers Accepting New PatientsPro
SQLEasy05Enrolled Primary Subscribers by StatePro
SQLEasy06Claims With Patient and Provider DetailsPro
SQLMedium07Claim Line Items With Procedure NamePro
SQLMedium08Patient Claims With Insurance Plan TypePro
SQLMedium09Prior Auth Requests With Procedure and ProviderPro
SQLMedium10Provider Contracts With Plan NamePro
SQLMedium11Denied Claims With Patient and Plan InfoPro
SQLMedium12Eligibility Checks With Patient and PlanPro
SQLMedium13Total Billed Amount by Claim StatusPro
SQLEasy14Average Paid Amount by Place of ServicePro
SQLMedium15Claim Count by Provider SpecialtyPro
SQLMedium16Denial Rate by Plan TypePro
SQLMedium17Total Patient Responsibility by PlanPro
SQLMedium18Top Procedures by Total Paid AmountPro
SQLMedium19Rank Providers by Claim VolumePro
SQLMedium20Top Claim per PatientPro
SQLHard21Patient Running Total PaidPro
SQLHard22Provider Claim Rank Within SpecialtyPro
SQLHard23Claims with Previous Service DatePro
SQLHard24Top 2 Line Items per ClaimPro
SQLHard25Claims Above Average Billed AmountPro
SQLMedium26Providers with Denied ClaimsPro
SQLMedium27Patients Above Plan Average Paid AmountPro
SQLHard28Active Procedures Never DeniedPro
SQLHard29High-Utilization PatientsPro
SQLHard30Claims Submitted in Last 90 DaysPro
SQLEasy31Average Processing Time by Claim StatusPro
SQLMedium32Claims Volume and Spend by Service MonthPro
SQLMedium33Patient Enrollment TenurePro
SQLMedium34Claims With Cost Tier LabelPro
SQLEasy35Providers With Network Status LabelPro
SQLEasy36Claims With Payment Ratio CategoryPro
SQLMedium37Providers With Claims or ContractsPro
SQLMedium38Patients With Claims but No Prior AuthPro
SQLMedium39Provider Reimbursement ScorecardPro
SQLHard40Plan Financial SummaryPro
SQLHard41Prior Auth Approval Rate by ProcedurePro
SQLHard42Patient Cost-Sharing BreakdownPro
SQLHard43Network Leakage Report by PlanPro
SQLHard44Claim Adjudication Pipeline AnalysisPro
SQLHard45Provider Contract Utilization AnalysisPro
SQLHard46Active Insurance PlansPro
PYTHONEasy47Claim Status CountsPro
PYTHONEasy48Provider Specialty SummaryPro
PYTHONMedium49Procedure Category BreakdownPro
PYTHONMedium50High-Value Approved ClaimsPro
PYTHONEasy51In-Network Office Visit ClaimsPro
PYTHONMedium52Primary Subscribers With Plan InfoPro
PYTHONMedium53Denied Claims With High Patient CostPro
PYTHONHard54Count Patients by Insurance PlanPro
PYTHONEasy55Total Billed Amount by ProviderPro
PYTHONMedium56Average Claim Amounts by StatusPro
PYTHONMedium57Claim Stats by Place of Service and NetworkPro
PYTHONHard58Provider Claims Performance SummaryPro
PYTHONHard59Claims With Patient NamesPro
PYTHONEasy60Line Items With Procedure DetailsPro
PYTHONMedium61Procedures Without Any ClaimsPro
PYTHONMedium62Claim Details With Provider and PlanPro
PYTHONHard63Full Claim DetailsPro
PYTHONHard64Rank Claims by Amount Within PatientPro
PYTHONMedium65Running Total Paid per PatientPro
PYTHONMedium663-Month Moving Average Billed per ProviderPro
PYTHONHard67Claim Amount Change vs Previous per PatientPro
PYTHONHard68Patient Enrollment Year and MonthPro
PYTHONEasy69Claim Processing Time in DaysPro
PYTHONMedium70Monthly Claims Volume by Claim StatusPro
PYTHONHard71Fill Missing Patient Contact InfoPro
PYTHONEasy72Normalize Claim Payment RatiosPro
PYTHONMedium73Clean and Enrich Patient Claims DataPro
PYTHONHard74Pivot Claim Counts by Status and Place of ServicePro
PYTHONMedium75Plan Claim Amounts Pivot by Plan Type and Metal TierPro
PYTHONHard76Classify Claims by Amount TierPro
PYTHONMedium77Patient Risk ClassificationPro
PYTHONHard78Compute Claim Payment RatiosPro
PYTHONMedium79Claim Amount Quartile BucketingPro
PYTHONHard80Time-Based Claim FeaturesPro
PYTHONHard81Patient Claims Feature MatrixPro
PYTHONExpert82Claim Line Item Feature EngineeringPro
PYTHONHard83Claim Amount Descriptive Stats by Place of ServicePro
PYTHONMedium84Billed vs Paid Amount Correlation by Place of ServicePro
PYTHONHard85Anomalous Claim Amounts (IQR)Pro
PYTHONHard86Claims Processing ScorecardPro
PYTHONHard87Provider Network Performance ReportPro
PYTHONHard88Full Claims Lifecycle ReportPro
PYTHONExpert89Insurance Plan Health ClassificationPro
PYTHONExpert90Cross-Provider Claims AnalysisPro
PYTHONExpertReady to practice Health Claims?
90 SQL and Python challenges built from real health claims data. Graded instantly in your browser — no setup required.