Safwan Abbasi

Safwanabbasi543@gmail.com
202-750-1380

PROFESSIONAL SUMMARY
 Over 7+ years of experience in analyzing large healthcare payer datasets within enterprise data warehouses, identifying
inconsistencies and improving data governance frameworks to ensure accurate claims processing and reporting.
 Collaborated with stakeholders to enhance data warehouse performance by optimizing payer data extraction processes, reducing
report generation time.
 Designed and executed medium-to-complex SQL queries in Google BigQuery to extract member eligibility data, streamlining
healthcare enrollment verification.
 Developed SQL-based analytical reports in BigQuery to monitor healthcare payer KPIs, enabling data-driven decision-making for
finance and compliance teams.
 Gathered and documented ETL transformation rules to support seamless data integration between healthcare payer systems and
downstream analytics platforms.
 Conducted impact analysis for ETL pipeline changes, ensuring compatibility with evolving payer data processing requirements.
 Designed optimized indexing strategies in SQL Server, improving query execution speed for payer reimbursement analytics.
 Developed complex SQL scripts in SQL Server to automate member claim validation, reducing manual data entry errors.
 Assisted in the implementation of cloud-based data solutions using Google Cloud Storage and BigQuery, enhancing scalability for
payer analytics.
 Led business process improvement initiatives for a healthcare payer, identifying inefficiencies in claims adjudication workflows and
implementing corrective measures.
 Conducted statistical analysis on healthcare payer claim trends, identifying patterns that supported predictive modeling for fraud
detection.
 Designed and executed UAT test cases for payer data integration projects, ensuring compliance with regulatory standards and
business requirements.

TECHNICAL SKILLS
 Programming Languages: HTML, XML, SQL.
 Data Base: MS Access, Oracle (SQL Series), DB2
 Reporting Tools: Crystal Reports 8.0
 Operating Systems: MS-DOS, Windows95/98/NT/2000/XP, Apple McIntosh, Linux
 Software: MS Office Suite (Word, Excel, Access, PowerPoint & Outlook), MS Visio, Rational Rose, Rational Requisite Pro, Adobe
Acrobat, MS Office FrontPage, Lotus Notes

PROFESSIONAL EXPERIENCE

McKinsey, New York, NY

Senior Business Analyst Sep 2021 to Present
Responsibilities:
 Led data warehouse analysis for a major healthcare payer, identifying gaps in claims processing and improving data integrity by
designing new validation frameworks, reducing claim errors.
 Analyzed payer enrollment, claims, and provider data, ensuring alignment with regulatory requirements and optimizing ETL
workflows to improve reporting accuracy.
 Developed complex SQL queries in BigQuery to extract, transform, and analyze large healthcare datasets, enhancing reporting
efficiency and reducing data retrieval time.
 Designed SQL-based automated data validation rules in BigQuery to detect anomalies in claim adjudication, improving fraud
detection rates and reducing compliance risks.
 Performed predictive analytics on patient outcomes using structured and unstructured health data, identifying cost-saving
opportunities and improving chronic disease management programs.
 Led ETL require gathering sessions with business and IT teams to define source-to-target mappings for membership and claims data,
improving data transformation processes.
 Defined data integration requirements between multiple payer systems and cloud-based data lakes, ensuring seamless data flow and
reducing ETL processing errors.
 Designed optimized SQL Server queries for healthcare payer data extraction, improving the performance of financial reporting
dashboards.
 Developed stored procedures and indexing strategies in SQL Server to enhance claims processing efficiency and streamline data
reconciliation.
 Migrated on-premises healthcare payer data to Google Cloud’s BigQuery, leveraging Dataflow and Pub/Sub to automate ETL pipelines
and improve scalability.
  Configured Google Cloud Data Studio dashboards to visualize key performance metrics, helping executives make data-driven
decisions on provider network expansions.
 Collaborated with actuarial and underwriting teams to optimize premium calculations using healthcare payer data, improving pricing
accuracy and reducing claim loss ratios.
 Analyzed risk adjustment models for a major Medicaid plan, identifying data discrepancies and implementing corrective measures
that improved risk score accuracy.
 Conducted root cause analysis on data anomalies in member eligibility records, ensuring compliance with CMS reporting standards
and reducing data mismatches.
 Developed interactive Tableau dashboards for trend analysis on provider reimbursement rates, assisting executives in network
contracting decisions.
 Facilitated stakeholder workshops to gather detailed functional and non-functional requirements for a data warehouse
modernization project.
 Authored detailed functional requirement documents for data validation and transformation logic, enabling seamless
implementation of ETL processes.
 Defined source-to-target mapping documents for healthcare payer datasets, ensuring data lineage tracking and improved
auditability.
 Led UAT efforts for a payer claims processing system, developing test cases and validating data accuracy before production rollout.
 Assessed payer data compliance with HIPAA and CMS regulations, ensuring secure data exchange and adherence to industry best
practices.

Deloitte, New York, NY

Business Analyst July 2019 to Aug 2021
RESPONSIBILITIES:
 Conducted gap analysis for a health payer’s data warehouse, identifying inefficiencies in claims processing and implementing data
validation measures that improved reporting accuracy.
 Optimized payer data warehouse workflows by mapping existing processes, identifying data redundancy, and implementing solutions
that reduced storage costs and improved query response times.
 Developed optimized SQL queries in BigQuery for claims and provider data analysis, enabling faster insights into reimbursement
trends and reducing query execution time.
 Built parameterized SQL scripts in BigQuery to extract patient eligibility data, supporting actuarial teams in risk assessment modeling
and improving premium pricing accuracy.
 Conducted statistical analysis on patient admission trends using payer data, enabling better resource allocation and cost control
strategies for a major healthcare provider.
 Partnered with business users to define ETL transformation rules for integrating provider and member data across multiple
platforms, ensuring data consistency.
 Collaborated with data architects to document ETL workflow specifications, ensuring seamless integration between payer claim
systems and enterprise data lakes.
 Designed complex joints and indexing strategies in SQL Server to enhance the performance of financial data extracts, reducing
processing time.
 Developed stored procedures and functions in SQL Server to automate the validation of payer enrollment data, improving
compliance with federal regulations.
 Assisted in migrating payer analytics datasets to Google Cloud, leveraging Cloud SQL and BigQuery to enhance scalability and
security.
 Designed and tested cloud-based ETL pipelines using Google Cloud Dataflow, ensuring seamless data movement from on-premises
servers to BigQuery.
 Conducted impact analysis on policy changes affecting claims adjudication, ensuring compliance with evolving state and federal
healthcare regulations.
 Assisted in designing a fraud detection framework using payer claims data, helping reduce fraudulent transactions and improve
regulatory reporting accuracy.
 Analyzed discrepancies in provider contract data, identifying patterns of underpayments and ensuring accurate reimbursement
calculations.
 Conducted in-depth trend analysis on patient readmission rates, providing actionable insights to help improve hospital discharge
planning.
 Facilitated workshops with cross-functional teams to gather detailed business requirements for a new payer reporting system,
ensuring stakeholder needs were met.
 Authored functional requirement specifications for payer claims auditing tools, enabling automated verification of claim
discrepancies.
 Created detailed source-to-target mapping documents for migrating historical claims data to a new analytics platform, ensuring data
integrity.
 Led UAT efforts for a payer compliance reporting tool, developing test scripts and validating regulatory compliance before
deployment.
  Assessed data security and privacy policies for a health payer, ensuring HIPAA compliance across all data-sharing processes.

Cognizant, Teaneck, NJ
Junior Business Analyst May 2017 to June 2019
Responsibilities:
 Assisted in analyzing claims and member data within a payer’s data warehouse, identifying trends that improved data-driven
decision-making and enhanced operational efficiency.
 Supported data reconciliation activities by validating data warehouse extracts, ensuring accurate and timely payer reporting to meet
regulatory requirements.
 Wrote medium-to-complex SQL queries in BigQuery to retrieve and analyze health plan data, optimizing query performance and
reducing execution time.
 Developed SQL-based transformations in BigQuery to improve data normalization, ensuring consistency in provider reimbursement
reports.
 Assisted in analyzing hospital admission rates using payer data, identifying trends that contributed to improved patient care
strategies.
 Documented ETL requirements by working with business stakeholders to ensure accurate data extraction and transformation from
various healthcare systems.
 Collaborated with data engineers to define ETL pipeline workflows, ensuring seamless integration of member eligibility data into
reporting systems.
 Assisted in optimizing SQL queries for healthcare payer data retrieval, improving the performance of provider contract analysis
reports.
 Supported the development of stored procedures in SQL Server to automate payer data validation, enhancing data accuracy.
 Assisted in configuring Google Cloud services for a payer data warehouse, ensuring secure and efficient cloud-based data storage.
 Worked with the cloud engineering team to validate data movement between on-premises databases and Google BigQuery,
improving data accessibility.
 Supported claims data analysis to ensure compliance with Medicaid and Medicare requirements, reducing claim rejections.
 Assisted in evaluating payer reimbursement policies by analyzing claims processing trends, identifying areas for financial
optimization.
 Conducted data validation on provider and member records, ensuring accuracy in payer enrollment reporting.
 Assisted in developing dashboards to track key payer performance metrics, improving data visualization for business users.
 Gathered and documented business requirements from stakeholders to support enhancements in claims processing workflows.
 Assisted in creating functional requirement documents for payer reporting tools, ensuring alignment with business needs.
 Worked with data architects to create source-to-target mapping documents, supporting the migration of historical claims data.
 Assisted in UAT activities for a payer data reporting system, validating test cases to ensure accurate data processing.
 Conducted data analysis to ensure adherence to HIPAA regulations, supporting compliance audits for the healthcare payer.

Education: Master’s in COMPUTER SCIENCE MIU, USA