Title: Senior Data Scientist (September 2021 - Present)
Company: State of Wisconsin Investment Board
Company Overview: The State of Wisconsin Investment Board (SWIB), created in 1951, is responsible for managing the assets of the Wisconsin Retirement System (WRS), the State Investment Fund (SIF), and other state trust funds. As of December 31, 2021, SWIB managed more than $165.6 billion in assets.
Role Overview: As a Senior Data Scientist, I lead the team and work on many different projects simultaneously. We work closely with the Risk, Asset Allocation, and Investment divisions to meet the goals of 650,000 beneficiaries of the Wisconsin Retirement System. The day-to-day tasks provide stakeholders with the necessary information to manage the risk of portfolios and help determine the appropriate asset allocation. My team works through the complete data lifecycle from cleaning and transforming third-party data to generating reports with actionable information for senior management. This involves corresponding with third-party data providers, using SQL on local and cloud-based platforms (Microsoft SQL Server and Snowflake respectively) for querying, analyzing data, and building reports with key metrics using Tableau and PowerBi. These metrics include portfolio risk and return which are measured through Volatility, Tracking Error, Drawdown, Value-at-RIsk, Greeks, Returns, Ratios, and stress tests. An important part of this role is to write Python scripts to implement scalable solutions that automate processes and ensure that the stakeholders receive the information in a timely manner.
Highlights:
Led a team to develop quantitative models for the Private Markets team. We used regression and principal component analysis to identify major sources of variability in the portfolio. Moreover, the model was based on data from MSCI and also helps the team identify:
Major correlations in the portfolio.
Value at Risk at the 90% and 95% level.
The impact of hypothetical and historical stress events on the portfolio.
Collaborated with senior executives to align data strategies with business objectives, driving cross-functional initiatives and streamlining risk management efforts by combining disparate data sources into comprehensive reports reducing weekly time spent. I used SQL to combine disparate data sources into one comprehensive, data center for risk management and built real-time reports on Power BI and Tableau.
Oversaw the creation and automation of customized investment performance reports for SWIB’s international portfolio, enhancing transparency and coordination between the risk and investment teams. Through stress tests and style analysis, helped the team identify external managers with a high information ratio that would work well with SWIB's risk budgets.
Developed and implemented credit rating methodology for High-Yield portfolios, leveraging FactSet data to identify SWIB's exposure to different credit ratings.
Developed and implemented a calendar rebalancing process that allows SWIB to take advantage of the changing financial markets.
Built bots using Automation Anywhere which has saved SWIB hours of daily manual work.
Mentored junior analysts, providing guidance in advanced analytics techniques, and contributing to their professional growth.
Company link: https://www.swib.state.wi.us/
Title: Intern, Enterprise Risk Management, Credit (June 2021 - August 2021)
Company: Federal Home Loan Bank of Indianapolis
Company Overview: The Federal Home Loan Bank of Indianapolis (FHLBI) is one of 11 independent regional cooperative banks across the U.S. FHLBI is privately capitalized and owned by member banks, credit unions, community development financial institutions (CDFIs), and insurers across Indiana and Michigan. As a cooperative, FHLBI passes the borrowing benefits in the global debt markets on to its members in the form of lower borrowing costs, which are subsequently passed on to consumers, businesses, and, communities.
Role Overview: As an Intern in the Enterprise Risk Management, Credit team I worked on developing a dashboard to track risk metrics for the Mortgage Program Policy. Through the Mortgage Program Policy, FHLBI purchases and holds consumer mortgage loans from its member banks. This provides the member banks with liquidity to issue mortgages in a responsible manner. FHLBI makes a narrow margin on the difference between the price paid to member banks for the mortgages and the mortgage payments from consumers. Since the bank receives mortgage payments over many years (10, 20, or 30 years), it is important to track the risk performance of the overall portfolio to ensure that it is within acceptable limits. This was particularly important since the COVID-19 effect on the housing market had led to many consumers being delinquent in their mortgage payments or loans going into forbearance. A dashboard with appropriate risk metrics would allow FHLBI's Risk Committee and the Federal Housing Finance Agency (regulatory body) to monitor and take timely actions.
Highlights:
Built interactive dashboards using Power BI to visualize investment performance metrics leading to a 30% decrease in time spent gathering and organizing data for decision-making.
Developed value-at-risk and expected loss reports on mortgage-backed securities; senior management used these reports to assess portfolio risks and guide mitigation strategies in dynamic market conditions.
Employed regression models to pinpoint significant factors: loan-to-value, debt ratio, and third-party loans - directly contributing to elevated delinquency rates within FHLBI's Mortgage-Backed Securities (MBS), enabling targeted interventions by senior management through refusing to buy poor-performing loans.
Built machine learning models (Decision Trees, KNN-Classifiers) achieving 96% accuracy in predicting mortgage payment delinquency; senior management employed the model for annual planning exercises and optimizing mortgage purchase strategies.
Worked with third-party vendor data and used Python and SQL to prepare, process data, and run numerous analyses. Based on these analyses I wrote a credit memorandum (and later developed a dashboard), which was accepted by the senior management, to track the following risk metrics:
Loan characteristics of the top five Sellers and Services along with a breakdown of the number of loans and ending balances in different U.S states.
Loan characteristics of the Sellers and Servicers with the highest delinquency rate in the past five years.
Changes in Loan to Value Ratio, Housing Ratio, and Debt Ratio of individual loans associated with Sellers and Servicers are mentioned in points 1 and 2. Through regression analysis and literature review, I found that these ratios are statistically significant factors that explain delinquency. Moreover, FHLBI should also track these ratios for Third-party loans (TPL) since TPLs have been prone to delinquency in the past.
The number and outstanding amount associated with loans in forbearance have been decreasing and this should be tracked over time (by Seller, Servicer, State, and Payment Method whether Scheduled-Scheduled or Actual-Actual payments).
Overall portfolio's Value at Risk and Delinquency Rate.
During the internship, I also reviewed unsecuritized counterparties, focusing particularly on their Capital Adequacy, Asset Quality, Management, Earnings, and Liquidity. Lastly, I worked to improve the quality of the data at FHLBI by developing preprocessing pipelines in Python (using Decision Trees and K Neighbors Classifiers). These pipelines allowed the team to compare U.S. counterparties with global peers.
Company link: https://www.fhlbi.com/
Title: Business Analyst and Finance Consultant, Enterprise Resource Management Team (August 2019 - October 2020)
Company: Systems Limited
Company Overview: Systems Limited (SL) is the largest software consulting company in Pakistan. It offers a range of services to clients in various industries including software, apparel, etc. These clients are spread out across the globe and SL is a partner for Microsoft. In my role at SL, I worked on several different projects.
Highlights:
One of the many clients was Jack Nadel International (JNI), a merchandising and sourcing company in the United States. I worked closely with JNI's senior management to identify areas of improvement that would help them reduce costs and achieve scalability. I developed key metrics for the client to track performance and make real-time decisions related to revenue management, budgeting, and product cost allocation. In this role, I determined the client requirements and then worked with a team of software engineers to implement the requirements onto Microsoft’s Dynamics 365 (Finance and Operations). I also led the initiative to revamp JNI's existing sales management system with a new custom-based solution to allow JNI's Sales Managers greater flexibility and efficiency in carrying out their daily tasks.
Team Viewer (TV) was another client in Germany. As a Finance Consultant for the TV project, I was responsible for providing insights and recommending ways through which TV could improve their performance. An example of a requirement that I delivered to TV was the addition of Revenue Scheduling Reports. These reports highlighted key aspects of subscription revenue and allowed the company to make meaningful decisions in real-time. This addition provided convenience to TV’s senior management and helped the company take dynamic actions. An indication of the overall value we have added to the TV so far is reflected by their geographic expansion and increase in revenue.
Alongside client-based projects, I took the initiative of developing a new Azure-based financial management system to target the growing Subscription Economy. I prepared process flows and product catalogs to determine how the system would work. I identified industries with major subscription use and mapped their business requirements onto the product so that customers could buy it off the shelf. Later I worked with software engineers to develop a first phase product. The product is still in its nascent stage but it is growing rapidly and has generated a revenue of over USD1 million for SL.
Company link: https://www.systemsltd.com/
Title: Assistant Relationship Manager, Corporate and Investment Banking Group (June 2018 - July 2019)
Company: Habib Bank Limited
Company Overview: Habib Bank Limited (HBL) is a leading bank in Pakistan with branches all over the world. As Assistant Relationship Manager (ARM) at HBL's Corporate and Investment Department, I managed a portfolio of 10 corporate clients worth USD 500 million. These varied from private manufacturing businesses in the food and apparel (for example, Mitchell’s Fruit Farms Ltd., Shoe Planet Ltd., etc.) to government projects in power production (for example, WAPDA, NTDC, etc.). A significant part of my job was to conduct detailed financial and risk analysis (top-down and bottom-up) to identify key factors of growth for my clients. Based on my analysis, I would build proposals requesting the bank's senior management to approve credit lines and project loans for my clients. An example of a major proposal was a Term Loan Facility of USD 100 million for Packages Limited through which they financed their machinery.
Highlights:
Frequently interacted with clients' management to understand changes taking place within the company and the industry.
Applied different risk management techniques including collateral coverage, ratio analysis, and comparative firm analysis to predict the performance of my clients. That would enable me to offer products that best suited their needs.
Company link: https://www.hbl.com/
Title: Senior Quantitative Instructor, SAT-I (November 2016 - Present)
Company: SmartPrep Academy
Company Overview: SmartPrep Academy provides students test preparation services for SAT-I, SAT-II, GRE General and, GMAT exams.
Highlights:
As a Senior Quantitative Instructor, I have taught over 200 students, many of whom have scored exceptionally high scores and have achieved admission in prestigious institutions throughout the world.
Company link: http://www.smartpreppk.com/
Title: Internship, External Audit (June - August 2016)
Company: A.F. Ferguson & Co. (PwC)
Highlights:
As part of a competitive summer internship program, I was selected among 250 students in my batch to be an intern at A.F. Ferguson & CO. (PwC). I participated in the mid-year audit of KSB Pumps and I focused on cash and tax reconciliation areas. By following the rigorous audit procedures of Ferguson, I reconciled half-year transactions of KSB Pumps with their existing cash balances. I checked the quality of the internal controls of the company; I compiled and presented a report on my findings to the senior management.
Company link: https://www.pwc.com.pk/en/
Title: Teaching Assistant, Suleman Dawood School of Business (August 2017 - May 2018)
Company: Lahore University of Management Sciences (LUMS)
Highlights:
I was the teacher's assistant for Intermediate Finance (FINN-200) with Dr. Salman Khan in Spring 2017, Introduction to Management Sciences (DISC-212) with Dr. Mohsin Nasir in Fall 2017, and Principles of Finance (FINN-100) with Dr. Aun Raza in Spring 2018. My responsibilities included: creating and grading quizzes and administering tutorials to support student learning.
Business school link: https://sdsb.lums.edu.pk/