New York, New York, United States
A talented data scientist with a Master of Arts in Statistics from Columbia University and a Bachelor of Engineering in Automation from Northeastern University. Capable of advancing new research, thought leadership, and innovative investment applications focused on the thoughtful use of techniques spanning machine learning, financial econometrics, and related quantitative and data-driven technique. Proficient at developing, testing, presenting, and maintaining a robust and varied pipeline of research applications based on machine learning. Adept at the thoughtful use of sophisticated techniques to solve investment problems and prototype new solutions in the financial services industry. Highly skilled at analyzing data and other processes to measure quality and accuracy, test, identify improvements, and benchmark the progress of solutions that have been implemented. Experienced at assisting in designing, improving and implementing internal controls through fact-based, data-driven entry, insights and analysis. Highly proficient at looking at the figures and information and drawing important patterns and conclusions. Possessing superior communication and time management skills used to excel in driving project life cycles and ensuring optimal data quality and integrity. Adept at providing essential consultative support and building key relationships through effective interpersonal, organizational, and leadership abilities. Committed to being a positive driver of company goals and exceeding expectations. Eager to apply specialized technical skills, educational knowledge, along with hands on practical financial experience to a long term and rewarding career in the finance industry
Proficient at mapping the market research for the financial industry to identify new innovative companies, services, methodologies and alternative data which high net worth investors and family offices can leverage to identify new opportunities, uncover emerging areas of growth and support investment decisions. Adept at running summary statistics and cross-tabulations of microdata or produce graphics and maps, on demand. Experienced in executing on projects, which involve data collection of ‘hard to get’ and niche populations such c-suit executives, managers in specific professional verticals. Highly skilled analyzing, mining and interpreting syndicated and custom data and determine the “why” of the results. CAREER HIGHLIGHTS: • Identified appropriate high net worth (HNW) or ultra-high net worth (UHNW) target investors for family office clients • Gathered and processed raw data (including writing scripts, Python web scraping, calling APIs, write SQL queries, etc.) • Assisted in email marketing campaigns, including boosting subscriber engagement and attracting new subscribers by developing effective strategies, verifying the authenticity of emails and validating delivery rate, open rate and click rate • Continued tracing reading volume of FON's weekly newsletters and uncovered that world's leading investment firms are the largest readership • Conducted comparative research on the features and costs of 10+ data vendors and pitched the recommended vendors to the CEO • Performed qualitative and quantitative analysis on business insights of global family office reports and world ultra-wealth reports • Created and managed SQL database and doubled the amount of data by integrating data from desperate data sources such of Bloomberg, Crunchbase, Preqin and WealthEngine
DATA ANALYST IN RISK MANAGEMENT: Adept at researching and developing the steps to test or monitor compliance with applicable policies/ procedures. Accomplished at completing assigned testing activities in accordance with established timelines and high standards of quality. Capable of assisting in identifying potential control weaknesses and making recommendations to strengthen. CAREER HIGHLIGHTS: • Analyzed exception-based monitoring reports for potential sales practice issues and ensure compliance with regulatory policies • Assisted in prioritizing and completing validation activities and maintaining the model risk governance processes in Matlab • Maintained statistics, identified patterns in Python and contribute to management reports for escalation of sales practice issues EQUITY RESEARCH ANALYST: Proficient at conducting valuation analysis within an industry, sector or asset class. Capable of converting industry knowledge into investment opinions. Skilled at building and maintaining financial model to evaluate historical information and generate projections. CAREER HIGHLIGHTS: • Used a multi factor test to validate the alpha drivers of companies in all 11 sectors of the S&P 500 • Conducted quantitative and qualitative analysis of public companies based on EVA methodology • Leveraged the firm’s propriety EVA model incorporating over 400 proprietary data points and key performance indicators (KPIs), measuring current and forecasted economic profit, value, growth rates and trends • Assisted in publishing research on public companies, including Snapchat, Nordstrom’s and NCL by listening to 2018 Q2 earnings calls, analyzing data from Bloomberg, FactSet and creating daily market overview by tracking global market news and intraday stock trends • Conceptualize and integrate technical, fundamental, and trading information into daily trading notes for clients and colleagues
Proficient at industry data collection & trend analysis, financial statement analysis, financial modeling & forecasting, assessment of business and financial strategy, and monitoring market movements through daily meetings with portfolio managers, economists, and strategists. Strong quantitative, analytical and problem solving skills. Detail oriented and ability to synthesis data and make deductive decisions. Focused with an ability to multi-task in a dynamic work environment. CAREER HIGHLIGHTS: • Analyzed financials in order to determine an internal credit rating for prospective purchases and currently held securities • Performed fundamental and relative value credit research on high yield and investment grade corporate credits across various industries including, but not limited to, insurance, retail, industrials and REITs