Kamlesh Lahoti

I am responsible for building, managing and updating Quant Factor Databases/ Quantitative Database and Quant Models, run bespoke quant analysis and publish quantitative research notes for institutional clients across sectors, industries, style, quality and cap cohorts

1) Vice President, Quantitative Research:

- Owned, incubated, manage and update global and US quantitative databases

- Publish quantitative research notes on regular basis for institutional clients

- Wrote and co-authored more than 100 end to end research notes and held phone and in person meeting with institutional clients

- Created statistical models for various predictive purposes, including identifying acquisition targets, quality stocks, value and growth stocks

- Proven ability to derive powerful investment ideas and recommendations for leading institutional investors

- Built a multi factor model to analyze portfolio factors exposures, use it to diversify portfolios and add specific factors to portfolios and also calculate idiosyncratic/stock specific risk

- Led the initiative to transition the full quant database, all models and prior research work from SAS to Python in record time and completed the project well before the deadline

2) Collaborative Research with ESG and SRI Teams:

- Built gender diversity model HERS and have been maintaining and updating it every quarter and have expanded it to include all major geographies. The model has generated positive alpha in all regions even during turbulent macro environment

- Worked with head of Socially Responsible Investing (SRI) team, to test historical efficacy of safety metrics, water usage and number of accidents in plant for Utility companies

3) Collaborative Research with Fundamental Analysts:

- Frequently collaborate with fundamental research analyst to provide quantitative perspective to their research pieces

- Performed analysis for Tech sector and specifically Software and Services Industry Group and gave a timely call to reduce exposure after the valuations ran over the top

- Recently did analysis with Energy team to understand capex and investment trends across energy sub-sectors

4) Team Leader and Individual Contributor:

- I manage and lead a team of 3 onshore and 5 offshore analysts working in different time zones and geographies

- I am responsible for directing, evaluating and reviewing their work and also hiring and training new resources in the team

- In addition to my role as manager and lead, I continue to play the role of Individual contributor in key projects

5) Client Requests:

- Worked on more than 100 bespoke and ad hoc client requests for Morgan Stanley's tiered clients

- Worked on many bespoke paid client requests for back-testing, portfolio attribution and appraisal, risk exposure and risk analytics

Senior Quantitative Research Analyst:

- Build a new quant factor database to capture factor movements on a daily basis with a library of more than 100 factors

- Build a model to classify industries into cyclicals and defensives based on multiple factors

- Build end-to-end automated earnings reports to track earnings and performance for S&P500 and Russell2000 constituents on a weekly basis. It included earning surprise statistics, beats/miss by sectors and industry groups, performance drift post beat/miss and progression of bottom-up index eps numbers, valuations, revisions and growth summary

- To find most efficacious factors by different GICS sector and sub-sector classifications for different time periods. Factor Efficacy was also done using our proprietary style, quality, cyclical defensives and cap cohorts' classifications

- Build dashboards for fundamental analysts for different sectors and industries providing quantitative inputs, valuations, revisions, fundamental data and stock screens

Data Scientist:

-Worked with clients in different domain and industries ranging from Pharma, Banking to Retail and CPG

-Build a Probability of Default (PD) model to identify risky customers and developed a framework to bucket customers into different risk bands for monitoring and risk mitigation

-Build a churn model to identify customers likely to churn and helped bank in creating and evaluate customer retention strategies

-Analyzed driver of sales for largest convenient retailer by performing regression analysis on sales, marketing and macro-economic data. Also identified the impact of different marketing channels on the sales