SUMMARY

• Analysis, development & integration using agile frameworks for data - intensive quantitative environments; project ownership to quickly implement, deliver and support risk and capital models, tools, solutions and Regulatory reports.

TECHNICAL SKILLS

Languages: Python. RAnalytics/Big Data ecosystem Pandas. numpy, statsmodels, SciPy, Scikit-Learn, Netezza. Hadoop

Modeling: Time Series, Logistic Regression. Optimization. Stochastic Processes

Agile tools: emacs, Jupyter, Matplotlib, seaborn, D3js, Git

Trading Systems: Order Routing. Precedence rules. FIX tags

PROFESSIONAL EXPERIENCE

Confidential, New York, NY

Senior Quantitative Analyst

Responsibilities:

• Implement two enhanced RC (Regulatory Capital) models for BAC’s exposure (Outstanding Balance exceeding USD 200B across 2MM+ accounts) in its Residential Mortgage (as defined by Basel 3 Final Rule) portfolio. Following an IRB approach, we estimate PIT (Point-in-Time) PD (Probability of Default) using scorecards and Logistic Regression; LGD (Loss Given Default) using Linear Regression (calibrated using collateral, loan, default rate and geographic risk drivers) followed by an OLS optimization; segmented (4 way across Utilization, delinquency status) EAD (Exposure At Default) based on a predicted LEQ; TTC1 (using long-run averages) PD scores are derived similarly to PIT PD; loans are rank ordered and clustered to derive the TTC3 PD scores used in the Capital calculations. Model output RWA (Risk Weighted Assets), is an input to EC (Economic Capital) estimates based on Monte Carlo simulation (e.g. Moody’s Risk Frontier). Iteratively implement the algorithms throughout the calibration, validation, Pro­forma, Production implementation and submission to Model Risk Management, Capital Management & Allocation Committees.
• Direct the integration of RWA results to downstream Capital reporting all the way to FFIEC 101.
• Detect numerous Data Quality issues with exposure level inputs and be the mentor for Technology and BA teams to efficiently correct the cleanse data and upstream processes during ongoing Pro Forma calculations.
• me evangelize Python, pandas, firm’s Quartz framework, and gnu tool-chains for rapid Implementation iterations.

Quantitative Consultant

Responsibilities:

• Led Market Risk integration/ Dev. team for ED. Total ownership of desk issues - Intra Day movements of P&Ls, attributions, exposures; errors reported by valuation models, scenario simulations - (issues with pricing/ static data feed/ traders’ marks; new instruments/contracts set-up by Middle Office and Operations; accurate nightly and Month-end reporting of Firm’s official P&Ls; Price Testing by Product Control; setup of new books). Training junior team members, establishing and enforcing appropriate service level agreements - effectively delegating, presenting solution to the business.
• Led the latency measurement, data mining/ reporting of OMS, SOR systems used by Index, Statistical-Arbitrage trading desks. Designed, coded, and managed dis effort. My analysis directly led to improvements in a) order flow to optimal liquidity pools, b) NTP synchronization configurations and c) reconfiguring applications based on through-puts, component latencies.
• Led the second level support of transactional systems for securities processing - diagnosed and troubleshot problems spanning trades' life-cycle (origination, connectivity, trade-breaks, booking, C&C, PnL's, greeks and nightly risk reports)

Confidential, Richmond, VA

Senior Analyst Energy Trading Floor

Responsibilities:

• Supported traders with efficient time-series data mining (S-Plus. MATLAB).
• Optimized portfolio models providing early warning signals for issuers at risk of significant spread widening.
• Organized data management. performed simulation. validation of Default Risk. cash flow models (S-Plus. FAME. Perl).
• Developed applications and tools for FX. Commodities desks to price trades and manage risk.
• Organized real time and daily feeds from Reuters. DRI and other sources (including GS traders’ marks) to support a global concurrent shared book with Real Time updates (slang. SecDB. Unix tools).
• Replicated the repository at global servers. promptly cleaned Data (by verifying prices and fixes across multiple feeds).

Confidential, New York. NY

Senior Support Engineer Technical Sales & Marketing

Responsibilities:

• Developed research and trading analytics tools. Product Integration for Inv. Banks. NY Confidential .
• Articulated FAME's technology. product capabilities using POC demos. results to Technology managers. C-level executives.
• Consulted for S&P Actuaries World Indices project - maintained equity index covering 34 countries for daily publication.
• Modeled multivariate scattered data (Radial Basis Functions. PCR/ PCA. Optimization. Fortran. MPI. MATLAB).
• Analyzed. designed. implemented 3-D transient multicomponent fuel spray models on Cray. SGI multiprocessors with active collaboration with Toyota Research Labs. MIT Sloan Automotive Lab. UW Madison research groups.
• Analyzed paleotemperature data for 300.000 years - patterns of natural climate variability were indicated.