DevOps/Quant Engineer

Rate, USD
Work schedule
Full Time, Contract, Temporary,
Invite to Job

Contact with talent

You must have an employer account and at least one active promoted job posted. If you don't have a listing, create one.

About me

Self-taught Quant/DevOps Engineer with 5Y+ of experience in IT, Trading and Asset Management. Dedicated to delivering products through operational excellence. Capable of building a toolchain from scratch for writing and shipping code to production through fast and efficient cycles.

Professional area




2015-09-01/2018-06-30 Master in Financial Markets at NEOMA BS

Master thesis: “Can we generate Alpha with Alternative Data ?”

– Analysis of the predictive power of Google trends and “Sentdex sentiment analysis”(NLP) for the S&P 500 underlyings over the period 2015-2018
– Webscraping (BeautifulSoup) / Analysis of the factor’s excess return with the python library Alphalens
– Spearman’s rank correlation, L/S spread analysis, data analytics with python (pandas, numpy)
– Ensemble learning (Random forest, KNN, SVM) to classify the observations
– Algorithmic trading with the web-based backtesting platform Quantopian

Option Pricing:
– Exotic options, Stochastic Differential Equations (Ito’s lemma), Black Scholes, Greeks

Fixed-Income & ccy derivatives:
– Cap/Floor pricing, FX/currency swaps arbitrage, Bond Futures (CTD arbitrage)

Financial Risk Management:
– Portfolio VAR backtests
– Normality test QQ plot/ jarque-bera
– GARCH(1,1), Maximum Likelihood Estimators
– Monte Carlo simulations, CreditMetrics modelling, CDS valuation


2021-04-01/2022-12-31 Quantitative Developer at Shell

Power Trading Desk Analytics: Optimizing revenue through reducing power imbalances.

Quant dev missions:
Forecasting :
– Forecasting solar PV and wind turbines energy production based on sensors and third-party weather data.
– Statistical analysis, Seasonal ARIMAX, Recurrent Neural Networks (LSTM), Principal Component Regression, Savitzkyโ€“Golay filter, STL decomposition.
– Signal processing algorithms: Augmented Kalman filter for sensors and data fusion to estimate temperature and irradiance.

Pricing (Mentored a team of 4 engineers to deliver the end product) :
– UK/European markets power price forward curves modelling. Taking low granularity marks and shaping half-hourly forward curves. Refactored SDLC from clunky Excel files to battle-tested python code deployed with cloud-based GitOps architecture

DevOps missions:
– Built a Github Actions CI/CD pipeline to improve the development workflow an productionize the code.
– Developed a branching pattern strategy for release management and improved SDLC by evangelizing DevOps principles across the team
– Improved deployment strategy with Gitops: better rollback strategy, testing framework

Technology used: Microsoft Azure, Databricks, Spark, Github, ML Ops, Terraform
Python libraries: numpy, pandas, pyastral, pyspark, statsmodels, keras, scipy

2019-07-01/2021-03-31 Software Engineer at PrismFP

– Options strategies, Interest rates derivatives
– Statistical analysis, PCA, Rates modelling, Volatility Models (SABR, Polynomial), in-house pricing library

Quant dev missions:
– Continuous deployment (Jenkins, Gitlab CI) of high quality Dockerized python code, linted (flake8, piprot) and tested (unit/integration) on a cloud-native development platform
– Implemented extensive option pricing library in python, stress tests scenarios and other key features for the trading analytics platform
– Microservices architecture using flask, implemented a distributed system instrumentation (with Opentracing and Jaeger) to monitor the speed of execution of our application workflow
– Caching LRU with memoization python library
– Deployed financial data pipelines with Airflow

DevOps missions:
– Deployed new containerized applications with Kubernetes / Docker / Helm
– Integrated Airflow on Kubernetes to enhance data pipelines scalability
– Implemented SQS queues with Lambda workers for infrequent workload processing

Technology used: Airflow, PostgreSQL, AWS, Kubernetes, Docker, Linux, Vagrant, VirtualBox, Loggly, OAuth2, Helm, Terraform, Opentracing, Grafana

Python libraries: numpy, pandas, flake8, PyPI server, unittests, mock, SQL Alchemy ORM(database agnositc), flask(microservices architecture), QuantLib, asyncio

2018-08-01/2019-06-30 Data Analyst โ€“ Capital Markets at Lyxor ETF

Lyxor ETF was the 2nd European Exchange Traded Funds provider and second in terms of market liquidity.

– Data pipelines owner (end to end)
– Pre-trade analytics / Spread analysis / Market microstructure (tick data) / Market impact / Stock-exchange mecanisms
– Database administration, SQL Performance Tuning / Ability to handle intensive computation with Python, vectorization of loops with numpy (slicing, masking)
– Developed a Bid/Ask premium arbitrage tool to identify over/under-priced ETFs. Defining methodologies and computing metrics from tick data
– Developed a web-app from scratch with flask (blueprint, MVC, logging design patterns, front+back end)
– Maintaining and improving the ETF Spreads monitoring tool (real-time data)
– ETL processes in python (OO programming), Advanced SQL queries, VBA, Tableau, BQUANT, Batch
– UML diagrams / Version control (Git) / Agile-Rad SDLC

2017-07-01/2017-12-31 Front Office Data Analyst Intern at Lyxor ETF

– Exposure to ETF Launches / New listings, replication strategies, performance analysis
– Assisting Fund Managers and Sales with Data Analysis in Python (pandas) and VBA developments
– Big Data analysis and visualization with Tableau
– SQL DB management
– Developed python algorithms for data quality monitoring / Web scraping / Web services (flask)

2016-01-01/2016-12-31 Cross-Asset Trader Intern at CBP Quilvest

– Managing FX and cash positions
– Trading FX and money market instruments, equities, bonds, options, futures, funds, ETFs, Gold
– Dealing orders from direct access clients
– Troubleshooting issues with Back Office and Middle Officers
– Back testing performance of structured products with VBA

Recommend this specialist

Recommend this specialist