Super Urgent Role - Research Analyst/Senior Research Analyst/Lead Analyst – Loan Data Remediation Analyst in Irving, TX/Charlotte, NC/NYC, NY (Crisil)


Role;- Super Urgent Role - Research Analyst/Senior Research Analyst/Lead Analyst – Loan Data Remediation Analyst in Irving, TX/Charlotte, NC/NYC, NY (Crisil)


Research Analyst/Senior Research Analyst/Lead Analyst – Loan Data Remediation Analyst

3 – 10 years of experience across the credit transaction life cycle, with a good understanding of credit risk data and systems

Support credit risk function of global banks in establishing and effectively managing the credit risk loan data remediation process:

  • Work closely with process owners, SMEs, and Data leads, taking ownership of data quality improvements and remediation efforts
  • Understand bank’s existing framework and understand information management practices including information lifecycle management, data modelling, master data management across a transaction life
  • Establish a standardized process to
  • Source facility related credit / legal documents and credit approval memos
  • Identify credit data related to the facility (for instance: collateral, covenant, exposure, limits, thresholds)
  • Analyze data from multiple sources to validate dimensions and impact of data quality issues
  • Analyze data to identify data quality issues and correlate those issues with data specifications and quality rules in the standardized process
  • Identify data gaps, inconsistencies across and within systems
  • Remediate through appropriate inputs across and within the systems that are part of the entire transaction cycle
  • Coordinate with other work streams to ensure data remediation efforts or outcomes adhere to project plans and requirements
  • Build an adequate governance structure for timely connects with stakeholders to discuss data remediation plans, manage escalations, and effectively close the remediation process
  • Partner with technology stakeholders and enterprise-wide business partners to conduct data diagnostic efforts, investigate root cause of findings, and present recommended options for solution(s) and remediation
  • Contribute to development and maintenance of data lineage, process maps, data concepts and glossaries
  • Maintain inventories of issues to catalog, monitor, assess, forecast and report on data quality issue remediation efforts
  • Develop and maintain metrics, scorecards, and dashboards to report on progress and impact of data quality remediation efforts

CA/MBA Finance/CFA/FRM

Should have 3 to 8 years of experience in credit risk function

  • Credit risk data operations experience, gained either through industry or within a consulting environment; Corporate, commercial/ SME or IB experience
  • Experience of relational database management, front to back system data flows, data handling, transmission, aggregation
  • Demonstrated experience of working with financial products life cycles and associated data needs
  • Experience with remedial / troubled loan data systems; Knowledge/ experience of a wide range of credit data operations 
  • Willingness to dig deep into data, and build additional insights into the credit portfolio
  • Experience in data governance programs with knowledge of data governance principles and practices
  • Excellent communication skills in English (verbal and written)
  • Independent and decisive mindset; strong analytical and problem-solving skills; a structured working style with passion for deep diving into problems
  • Team player
  • Ability to work on tight deadlines
  • Excellent written and oral communication skills





I would appreciate if you could reach out on my below mentioned contact coordinates, if the position be of interest to you. 

Have a great day ahead!

---------------------------------------------------------------------------------------------------------------------------------

Sundeep Diwan

+1-908-633-4217

sundeepl@vbeyond.com

www.linkedin.com/in/sundeep-diwan-87a08b227/ ( For Latest Job Roles Please connect with me on Linkedin )

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