Risk Management Power Bi

Zain Mahmood

London Dubai • +44-743*-****** / +971-**-***-****

************.*******@*****.*** • linkedin.com/in/zain-mahmood-risk-data HEAD OF QUANTITATIVE RISK & DATA

PROFILE:

Strategic risk & data leader in global energy markets with a decade of experience turning complex commodity data into decisive trading and investment action. Deep expertise across risk policy, quantitative modelling and full stack data platforms with a focus on measurable impact.

KEY STRENGTHS & TECH STACK:

WORK EXPERIENCE:

Head of Quantitative Risk & Data Energetech, Dubai Aug 2024 – Present Reported into CEO. Lead a 5-person Risk Analytics team (2 Risk Quants, 2 Data Engineers, 1 Back-office Analyst).

• Built a wholistic, systemised risk suite that governs VaR across 12 trading books, adopted by Front Office and Finance/Treasury.

• Designed and implemented risk management frameworks, including capital allocation models and drawdown limits for commodity traders.

• Shaped pricing and hedging strategies, assessing minimum pricing impacts, and evaluating venture economic impacts for origination deals.

• Advising on Risk controls and business approach to new markets and trading behaviour.

• Automated the generation of daily risk reports, including Value-at-Risk (VaR), P&L, and stress-testing metrics.

• Worked on structuring ETRM products to enhance the integration between the Risk and Front Office functions.

(Tech: Python, Flask, Kafka, React, Power BI, Github Actions, Docker, Azure) Lead Quantitative Analyst (Risk) ENI, LONDON Apr 2023 – Jun 2024

• Led liquidity-risk modelling for gas & power book, deploying Monte-Carlo engine that feeds liquidity metrics to four trading desks.

• Voting member of the Group Risk Committee; presented bi-monthly enterprise-risk pack (market, FX, operational) covering 12 desks and revising limit structures.

• Created and ran a weekly Python up-skilling programme, delivering a self-written curriculum that trained 12 – 15 colleagues.

• Using Monte Carlo Simulations to model VAR and Liquidity Risk.

• Designed procurement and trading strategies to address liquidity and price risk in volatile energy markets.

• Responsible for automating and running daily risk reports, including risk and P&L reports.

• Creating front end tools using VBA for ease of managing large databases through excel for those not able to use SQL.

• Took ownership of legacy Python code; refactored codebase, reduced runtime errors by 95% for the team.

(Tech: Python, Kafka, Power BI, SQL, VBA, GitLab CI) Category Tools & Technologies

Leadership & People Team leadership, mentoring & Python up-skilling, contract negotiation with brokers & external vendors (ICE, Bloomberg, Reuters, forecasting providers), stakeholder management

Risk & Modelling VaR & liquidity models, Monte-Carlo / scenario / “what-if” analysis, initial-margin

(IM) calculations, PPA pricing models

Programming, ML &

Pipelines

Languages & APIs: Python, R, SQL, VBA, C++, REST (Flask-RESTx, FastAPI) ML libs: PyTorch, TensorFlow, Pandas

Streaming: Apache Kafka (Connect, Schema Registry), AWS Kinesis Cloud & DevOps AWS (EC2, S3, RDS, CloudFront), Azure Functions, Docker, Kubernetes, Terraform, GitLab CI, GitHub Actions

Datastores & BI PostgreSQL, MySQL, MongoDB, Time series DBs, Power BI, Tableau, Plotly Senior Data Scientist, Forecasting & Risk Thames Water, Reading Sep 2021 – Apr 2023 Reporting line into Head-of-Commercial; 1 report (intern)

• Built ANN demand-forecast model for water consumption.

• Standardising reports and key performance indicators tracking monthly historical movements in consumption and revenue.

• Reviewing existing forecasting methodologies and finding the statistical strength of each one as well as caveats.

• Forecasted long-term consumption trends across portfolios valued at £4 billion, providing insights for value chain planning and short-term market strategy adjustments.

• Procurement and management of data from various internal sources and web scrapes.

(Tech: Python, R, TensorFlow/ANN, Pandas, SQL, Power BI, Azure) Forecasting, Risk & Reporting Analyst Corona Energy, Watford Feb 2019 – Sep 2021

• Creating a predictive modelling method to forecast gas and power consumption using a combination of Artificial Neural Networks and SARIMAX models.

• Automated Jenkins CI/CD pipeline for Python forecasting stack

• Standardising reports and key performance indicators tracking yearly PNL, Imbalance and other quantitative measures.

• Short, medium and long term forecasting of the entire Corona Energy customer portfolio.

• Daily/weekly/monthly reporting for the entire Corona Energy customer portfolio.

• Managed external data contracts (weather, market curves) and automated web-scrapes, cutting data-prep time by 70

%.

(Tech: Python, R, Jenkins CI/CD, SQL, Power BI, Pandas) Volume Risk Analyst (Redundancy) Smartest Energy, London Jul 2017 – Dec 2017

• Employ and execute hedging strategies on the European power book to determine wholesale trades that re-align the portfolio with the Volume Risk team’s risk appetite.

• Re-engineered demand-forecast models (Python + SQL).

• Authored a robust Volume-Risk methodology (VaR, NFP, stress) now embedded in pricing of fixed, flex and bespoke contracts.

• Developed tools for the production and distribution of accurate and timely reports, for example, the Volume Risk position and P&L to relevant internal and external stakeholders.

(Tech: Python, SQL, Tableau, VBA, ETRM)

Trader Training Analyst (Contract) Mandara Capital, London Feb 2017 – June 2017

• Captured requirements for 15 workflows; produced process maps and test packs.

• Developed front- and back-end simulator (VBA + SQL) that replays historical market & liquidity shocks.

• Thoroughly documented all aspects of projects, including time-boxed delivery targets, designs, and architecture.

• Frequent reprioritization and additional sprint planning due to requests for additional features.

(Tech: VBA, SQL, Excel, ETRM)

Oil Derivatives Trader Mandara Capital, London Sept 2016 – March 2017

• Active market maker in an illiquid market, specialising in curve trading. Generated $1.5m P&L in six months through calendar-spread arbitrage.

• Executed de-risking trades for our book in the most efficient way, considering the number of trades and costs associated.

• Created an innovative hedging strategy which saves my company $800,000 per annum within the first six weeks at Mandara.

(Tech: VBA, SQL, Excel, MATLAB, ETRM)

OTHER SKILLS AND ACHIEVEMENTS:

• Languages: English, Urdu, and Punjabi: Native, Arabic: Intermediate

• Member of Mensa

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