Nimish Acharya

About Nimish Acharya

Data & Analytics Professional with hands-onexperience processing and extracting intelligencefrom financial documents worth over $50 Billion Plusat an AI-focused fintech.I work at the intersection of credit domainknowledge and production AI systems — acombination that is genuinely rare at my stageof career.At CredCore, I contribute directly to the datapipelines and AI workflows that power financialdocument intelligence at scale. My work involvestraining and processing unstructured legal andcredit agreements, validating AI outputs,improving extraction accuracy, and translatingclient feedback into product improvements. Oneoutcome I am particularly proud of — contributingto a 50%+ reduction in processing time and SLAturnaround through pipeline optimisation anddomain-driven accuracy improvements.Day to day I work with Python, Pandas, SQL,regex-based extraction systems, and unstructuredfinancial data — ensuring the quality,consistency, and reliability of creditintelligence that teams depend on for decisions.Technical Skills:Python | Pandas | SQL | Regex | Power BI |PostgreSQL | ETL | Data Pipelines |Credit Risk Analytics | AI System Validation |Unstructured Document ProcessingOutside of data — I am a cinematic videographerand visual storyteller. The same principlesconnect both worlds: precision, clear structure,and a defined outcome.Open to connecting with data professionals,recruiters, and analytics teams building the systems.

Experience

1. Senior Credit Analyst

   Credcore

   Apr 2026 — Present

   As a Senior Credit Analyst at CredCore I work atthe intersection of financial domain expertiseand production AI systems — contributingdirectly to the pipelines and workflows thatprocess credit and legal documents at scale.Key Contributions:• Trained and processed financial documents worth over $50 Billion Plus in value — contributing to one of the core document intelligence pipelines at the company• Contributed to a 50%+ reduction in processing time and SLA turnaround through pipeline optimisation, accuracy improvements, and domain-driven feedback — directly improving product performance for clients• Collaborated with data and engineering teams across multiple domains to enhance AI model accuracy and improve extraction pipeline reliability — bridging the gap between domain knowledge and technical execution• Managed client feedback discussions and translated real-world credit use cases into product improvements — ensuring the AI system reflected ground-level financial document realities• Performed structured data validation and quality checks on large volumes of unstructured financial data — maintaining accuracy, consistency, and reliability of credit intelligence outputs• Worked daily with Python, Pandas, SQL, and regex-based extraction systems in a production financial data environment — processing PDFs, DOCX contracts, and structured financial schedules• Validated AI-generated outputs across financial document workflows — identifying extraction errors and inconsistencies before downstream credit decisions were impacted

Education

• Delhi Public School Bhopal

  12, ACCOUNTANCY, BUSINESS,ECONOMICS, INFORMATION PRACTICES

• SAGE University Bhopal

  B.COM(INTERNATIONAL BUSINESS & FINANCE), Accounting and Finance

• ACCA

  Knowledge Level Student, Accounting and Finance

• The Institute of Chartered Accountants of India

  CA Foundation, Accounting and Business/Management