Akansha Mishra

Home Lending Origination Data Team
Dec 2024 – Present

• Analyzed data to identify areas of improvement, implementing changes that resulted in greater operational efficiency.
• Successfully managed change within the organization, ensuring smooth transitions during periods of restructuring or process improvements.

Commercial Credit Risk Data Engineering Team
Prior Role

Responsibilities & Contributions:

• Supported home lending and commercial credit risk analytics using SAS Enterprise Guide, Teradata, and Jupyter Notebooks.
• Extracted, cleansed, and transformed data from Teradata, Oracle, and SAS files using SAS and Python to create modeling-ready datasets and tables.
• Built and maintained SAS datasets and Teradata tables for commercial credit risk and loss forecasting models.
• Developed quarter-over-quarter comparison dashboards to support data validation and trend analysis.
• Created key commercial risk variables (e.g., default date, obligor status, lifetime loss, nine-quarter loss) aligned with portfolio definitions.
• Collaborated with credit risk modeling teams to translate business requirements into scalable data solutions.
• Normalized and aggregated data to address business-driven changes and ensure model stability.
• Implemented data validation and quality checks using SAS and SQL, and delivered monthly/quarterly data insights to stakeholders.
• Contributed to the migration of SAS workflows to Python.

Key Projects:

• Developed an internal Freddie Mac and Fannie Mae market comparison dashboard, reducing dependency on external vendors and driving cost savings.
• Led analysis of a new charge-off data source, assessing structural differences and downstream impacts.
• Analyzed charge-off and recovery patterns to determine gross vs. net reporting and delivered a validated data source for commercial risk models.

Credit Card Risk & Data Analyst – JPMorgan Chase & Co.

• Performed risk impact analysis and delivered data-driven remediation for credit card customer issues in a highly regulated financial services environment.
• Analyzed large-scale financial, customer, and transactional data using SAS, SQL, Teradata, and Oracle to identify, segment, and validate impacted populations.
• Conducted root cause analysis, quantified financial exposure, calculated customer refunds, and assessed non-financial risk impacts.
• Validated impacted accounts across front-end systems and supported end-to-end customer remediation in alignment with internal controls and compliance standards.
• Leveraged customer demographic data to support regulatory reporting, customer communications, and remediation notifications.

Project – Promotional Benefit Loss Due to Billing Cycle Change:

• Led analytical investigation into promotional benefit loss risk caused by credit card billing cycle changes.
• Identified a logic gap between cycle-based benefit allocation and date-based promotional end calculations, resulting in missed promotional credits.
• Developed SAS and SQL workflows to identify impacted customers, determine impacted periods, and compute account- and transaction-level financial impact.
• Performed detailed analysis of promotional transactions, refunds, and eligibility rules to ensure accurate remediation.
• Supported financial and non-financial customer remediation in compliance with risk management, audit, and governance requirements.

Tools & Technologies:
SAS, SAS Enterprise Guide, SQL, Teradata, Oracle, Data Analysis, Risk Analytics, Financial Impact Analysis, Root Cause Analysis, Regulatory Compliance

Data Analyst – Healthcare & Real-World Evidence Analytics

• Led requirements gathering and stakeholder engagement, producing business requirement documents (BRD), functional specifications, and process flow diagrams for analytics initiatives.
• Validated, profiled, and assessed Real-World Evidence (RWE) data to ensure data quality, completeness, and regulatory readiness.
• Developed and optimized SAS programs based on detailed specifications; created test plans and supported UAT and unit testing.
• Performed data cleansing, anomaly detection, and data quality checks to ensure reliable analytical outputs.
• Delivered analytics and reporting across healthcare domains, including line of therapy analysis, drug efficacy, commodities, and outcomes research.
• Generated statistical and analytical reports to support sales forecasting, pricing strategy, market access, and cost modeling for new pharmaceutical products.
• Designed and published Tableau dashboards to visualize trends, patient outcomes, and key performance indicators for business and clinical stakeholders.
• Collaborated with cross-functional teams to translate complex healthcare data into actionable insights.

Tools & Technologies:
SAS, SQL, Tableau, Data Analysis, Healthcare Analytics, Real-World Evidence (RWE), Statistical Analysis, Data Quality, Forecasting, Business Requirements, Advanced Analytics

Program Analyst (Intern → Full-Time)

• Performed data management, data cleansing, transformation, integration, and reporting using Base SAS, SAS/SQL, SAS Macros, and advanced SAS functions.
• Delivered end-to-end analytics and data engineering solutions, managing SAS projects from requirements gathering and design through development, testing, and production deployment.
• Partnered with clients and stakeholders to capture business requirements, producing functional specifications and analysis documents.
• Designed, developed, and debugged SAS programs, resolving data quality issues and improving processing efficiency.
• Built and maintained ETL pipelines to extract, transform, and load data for reporting and downstream analytics.
• Extracted and integrated data from multiple source systems including Excel, flat files, and DB2 databases, creating reusable and scalable datasets.
• Owned secure inbound and outbound electronic file transfers (EFT) between clients and internal systems, ensuring data accuracy, timeliness, and compliance.
• Developed recurring and ad hoc analytical and operational reports using SAS procedures.
• Supported knowledge transfer, training, and mentoring of new hires, improving team productivity and code standards.

Tools & Technologies:
Base SAS, SAS/SQL, SAS Macros, ETL, Data Engineering, Data Analytics, DB2, Data Integration, Reporting, File Transfers, Requirements Analysis