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Power Plant Manager

Location:
Spring, Texas, United States
Posted:
November 12, 2018

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Resume:

A. N. Comanici

281-***-**** ac7n1l@r.postjobfree.com Green Card holder

Summary: Business oriented professional with experience in model development, implementation & validation; market & credit risk, pricing & hedging for derivatives and structured deals, stress testing, machine learning &data analytics in energy and financial markets; retail and wholesale energy markets; load forecasting, econometrics, statistics, time series analysis, optimization, numerical simulations; business intelligence, reporting, combined with academic research

Technical: Matlab (8 years), Python (4 years) (scikit, mlpy, MDP, pandas, numpy, scipy, nltk);

SQL (8 years); Excel VBA (8 years); SAS (4 years), R (1 year); C++/ C# (3 years);

Endur (3 years), Allegro (2 years) ; Power BI (1 year), Tableau (1 year)

Experience:

Risk, pricing and hedging; stress testing:

Market risk (VaR, PaR, Greeks) and credit risk (PD, LGD, EAD); Volatility & correlation models

Energy and financial derivatives; structured transactions: tolling; power plant; gas storage; swings options

Retail and wholesale products in gas, power; solar, wind; volumetric & price risk; load forecasting

Stress testing, back-testing, scenario analysis

Knowledge: Nodal markets pricing; congestion revenue rights and financial transmission rights in ERCOT

Models & mathematical methods:

Monte Carlo simulations, bi/trinomial trees, finite-differences; stochastic differential equations

Analysis of time series; financial econometrics; co-integration

Dynamic programming; portfolio optimization; stochastic optimization; constrained optimization

Machine learning & data mining:

Classification: support vector machines (SVM), decision trees; Prediction: regressions; Clustering: k-means

Deep learning: neural networks; genetic algorithms, Bayes techniques

Dimension reduction: principal component analysis (PCA), factor analysis

Natural processing language (NPL) for unstructured data

Professional Experience:

Jul 2018 – December 2018 (contract) Repsol, Houston, TX

Senior Consultant

Risk management (Allegro, Excel VBA, SQL, FEA, RiskWatch, Python)

Run daily reports for the business (oil & gas): positions, Value-at-Risk (VaR), economic PnL (profit & loss), financial books

Run valuation models for a portfolio of storages, swing options, transportation deals

Analyzed the reports and communicated risks to Front office

Collaborated with Product control and Back office on various issues related to daily reports

Automated all reports used by Middle office

Model validation & implementation (Excel VBA, SQL, FEA, Python)

Reviewed the methodology, validated and tested FEA models for gas storage and swing options (rolling basket of spreads, rolling intrinsic, spot optimization) and for gas transportation (spread options)

Calibrated mean-reversion models for gas and oil prices used in structured deals valuation

Performed statistical analysis on time-series of gas and oil prices

Fundamental analysis of gas and oil price formation and direction, gas supply & demand modelling

Jan 2017 -- May 2018 Direct Energy, Houston TX

Quantitative Risk Analyst/Manager

Risk management, model validation and data analytics (Matlab, SQL, Excel VBA, Endur, Power BI)

Contributed to implementation of risk control framework and methodology

Collaborated with Structuring, Product control and Front office on risk, models and hedging

Assessed risk embedded in new products & transactions and made recommendations to Front desk

Performed validation for a valuation model (spread option & extrinsic haircut) including Greeks

methodology for an ERCOT tolling contract with embedded ancillary services

Validated the methodology for marking ERCOT power & NYMEX gas implied forward volatilities

Performed validation for the weather options pricing models used by the company

Reviewed all risk models: Value-at-Risk (VaR) and Profits-at-Risk (PaR) and option pricing models

Contributed to the implementation for a weekly retail hedge ratio reporting model (load, supply, hedges)

Performed validation for marginal default frequencies (MDF) methodology used by Credit risk team;

MDF are used in potential future exposures (PFE) model

Statistical analysis of ERCOT power & NYMEX gas prices (statistical inference and time series analysis)

Model development and implementation (Matlab, SQL, Excel VBA)

Enhanced the library of pricing and risk models for Market Risk & Credit Analytics

Developed a daily margin VaR (DMVaR) model that produces exposures and VaR calculations

by counterparties and credit support annexes

Implemented a spread option model for valuation of tolling contracts and a multi-commodity multi-

factor forward valuation model

Researched volumetric risk modelling (load - price)

Performed load forecasting modelling (traditional vs machine learning methods)

Implemented a delta hedging model for North-East tolling contracts

Automated risk models (DMVaR, VaR, PFE) to run daily via batch files

Supervision & other duties

Guided team members to understand Matlab code used in risk models to produce daily reports

Run ERCOT reports when ERCOT manager was in vacation

Run the option spread model, delta hedging model and daily PnL report for various tolling contracts

2016 -- 2017 LCRA, Austin TX

Quantitative Risk Analyst

Pricing and hedging (Python, Matlab, SQL, Excel VBA)

Development and implementation of pricing models for options – gas and power & heat rates

Reviewed and risk assessed the hedging strategies used by company

Validated the methodology for two dispatch models used by the company

Weekly run of the old and new dispatch model for generation assets to compare the models’ outputs

Validated load forecasting model used by company

Risk management (Matlab, Python, SQL, Excel VBA)

Development and implementation of risk models for market risk– Value-at-Risk (VaR) and Greeks

Weekly run of VaR model with and without hedges to keep track of portfolio diversification effect

Researched risk metrics to quantify liquidity risk in the company

Back-testing and stress testing for risk models

Data analytics & position reporting (Allegro, Excel VBA, Tableau, SAS, Python)

Contributed to implementation of a business intelligence platform that it is used to get a better understanding of the outputs from risk and pricing models

Statistical analysis of historical load, capacity, NYMEX gas and ERCOT power prices

2014 -- 2016 CMHC, Canada, Quantitative Specialist

Canada, Independent Consultant

Model development and implementation (C++.NET, Matlab, Excel VBA, SAS, GEMS - ESG)

Development and implementation of risk models for market risk-- Value-at-Risk (VaR) for investment portfolios; credit risk -- probability of default (PD), loss given default (LGD) and exposures at default (EAD); economic capital

Model implementation for potential futures exposures (PFE) for interest rates derivatives (swaps) involving mortgage backed securities (MBS) and bonds (CMB) (fixed income modelling)

Worked on economic capital stress testing

Studied correlation matrix in normal and stressed conditions

Consulting services on various projects in energy and finance (Matlab, Python, C++, SQL, Excel VBA)

Portfolio Value-at-Risk (VaR) and Profit-at-Risk (PaR); Greeks calculations

Credit risk in energy and financial transactions (PD, LGD, EAD)

Pricing and hedging using derivatives; risk management in structured transactions

Predictive analytics; data analytics/mining

Data mining & machine learning (Matlab, Python, SQL, Excel VBA)

Researched trading strategies (via machine learning methods) & portfolio optimization

(SVM, neural networks and econometric models comparison for stock prices)

Implementation of risk management tools for trading strategies

2013 -- 2014 Gazprom M&T, London UK

Quantitative Analyst

Pricing and hedging - model development & implementation (Python, C#.NET, Excel VBA)

Developed models to support retail expansion strategy in power, gas, carbon and embedded generation (fixed, indexed and variable products) to increase company profits

Priced retail products in European gas &power markets (multi-commodity multi-factor forward model)

Performed pricing for energy derivatives and developed hedging strategies

Valuation for storage, tolling agreements, interconnectors; power plant economic dispatch modelling

Calibrated pricing & demand models for gas and power markets

Contributed to gas & electricity demand forecasting model (times series methods)

Priced power production deals based on wind and solar production (Markov chains)

Implemented retail portfolio effect into pricing model to achieve portfolio optimization

Risk management & data analytics (Python, SQL, Excel VBA, Endur)

Kept track of daily changes for Greeks for various hedging options strategies

Reviewed the Value- at- Risk (VaR) methodology

Assessed the risk of individual customers to understand retail portfolio effect

Statistical analysis of European gas and power prices

2010 -- 2013 FSA/Bank of England, London UK

Quantitative Analyst

Model development, validation and implementation (Matlab, Excel VBA, SAS, R, SQL)

Performed model validation and review of risk models (Value-at-risk (VaR), Credit VaR) and pricing models for derivatives (commodities, FX/rates, equities) for financial institutions (regulatory capital models from various foreign and domestic banks)

Implemented a VaR model for a portfolio for a hedging exercise used to investigate how VaR changes under various strategies, scenarios and hedging horizon, volatility time horizons and correlation matrices (used by fundamental review policy FSA)

Contributed to the development of wholesale credit risk model – PD and LGD; as well as credit index model via Kalman Filter and state space models (PD – probability of default; LGD – loss given default)

Implemented econometric models (regressions and auto-regressive models)

Estimated parameters via maximum likelihood method and optimal least squares (OLS)

Researched systemic risk contagion in financial networks from interbank lending and liquidity shocks

and the influence on regulatory policy changes for financial stability

PD models:

oAnalyzed a numerical method for the variable scalar adjustment for new internal model PiT PD

oAnalyzed the forecasting power of two PD factor models: one with four macro-economic factors; the other with one macro-economic factor (logistic regressions)

Implemented different measures for mortgage analysis to compare risk and performance among various financial institutions

Contributed to implementation of automated platforms for mortgage analysis and structured finance products

Data analytics & statistical analysis (Matlab, SAS, SQL, Excel VBA)

Statistically analyzed various datasets used in the models developed (risk and econometric models)

- data preparation and explanatory analysis, cross-correlation between variables, distributions estimation

Clustering techniques applied to a dataset of mortgages and loans

Performed statistical analysis of balance sheets of banks and building societies to understand how changes in liabilities structure influence the assets structure (clustering k-means, times series analysis, statistical inference methods, principal component analysis - PCA)

Designed relational databases models for various risk models built in FSA

2004 -- 2010 Virginia Tech & Univ of Houston & Rice University, USA

Univ of Glasgow & Isaac Newton Institute UK Postdoctoral Fellow

Education:

2000 – 2004 PhD in Applied Mathematics, GPA: 4/4

University of Ottawa, Canada

1998 – 2000 BSc in Computer Science, First Class (1:1)

Babes-Bolyai University, Cluj-Napoca, Romania

1997 – 1998 MSc in Mathematics, First Class (1:1), GPA: 10/ 10

University Paris VI & Babes-Bolyai University

1993 – 1997 BSc in Mathematics, First Class (1:1), GPA: 10/10

Babes-Bolyai University, Romania

Scholarships & Awards:

2004 – 2010 Prestigious travel awards to attend and present research at international conferences

2000 – 2004 Canadian postgraduate and Excellence scholarships

1993 – 1998 Romanian Honor Scholarships (MSc and BSc)

1989 – 1993 National Competitions in Mathematics (top 25%)



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