Megha Maran
Quantitative Strategist, Associate @ Goldman Sachs
United States
New York
Financial Services
Python (Programming Language), Java, R, C++, SAS Programming, Data Science, Data Analysis, SQL, GitHub, LaTeX, MongoDB, Microsoft Office
Experience

Quantitative Strategist Summer Analyst
New York, New York, United States
- Equity Derivatives Automation desk: Automated quoting of Asian options in Goldman’s proprietary trading language Slang to support higher trade volumes from insurance companies, facilitating new business worth $2M per year - Systematic Market Making FX desk: Built an intraday trading strategy in Java and Python, leveraging real time market making signals to achieve a backtested sharpe ratio of 3.88 over the course of 1 year

Data Science Intern
- Developed an algorithm to extract seasonal cycles of ice sheet velocity with Python by detrending the velocity time series and implementing regression models, using image pairs from JPL’s ITS_LIVE database - Applied the models in a geospatial context to predict future ice sheet movement and sea level rise

Digital Solutions Systems Analyst Intern
- Developed a workflow to send information from Earthsoft's Environmental Quality Information System to third party applications - Created JSON objects from environmental datasets and used a REST API to query data and build templates - Developed macro enabled reporting templates and crosstab reports in Excel - Constructed web dashboards used by project teams to visualize and analyze environmental data

Data Science Intern
- Rewrote the company’s credit algorithm, using Python to utilize a cash-flow based underwriting instead of credit scores - Extracted data from credit reporting agencies and bank statements and parsed the data with NLP - Designed categories of expense and obligations calculator reports that were then used to create a regression model

Undergraduate Student Researcher
Cambridge, Massachusetts, United States
- Set up a scraper in Python to collect stock data periodically from the Robinhood API - Translated SAS code about quantitative stock selection into R - Collected and analyzed financial data for the purpose of stock selection and portfolio allocation

Summer Learning Academy Extern
- Acquired business and technical acumen along with personal growth and professional development - Completed entry-level training in human resources, finance, advertising, media and technology, communication and leadership - Gained insights and advice on business, leadership, and career from business executives and recognized experts
Megha Maran's Contact Information
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