Allow me to introduce myself—I am Teddy Ambona, a driven and self-taught Python/DevOps Engineer. With over 5 years of focused expertise in SaaS, cloud development, automation, and APIs, I bring a wealth of knowledge to the table.
My proficiency as a Certified Kubernetes Administrator and AWS Solutions Architect enables me to build cutting-edge toolchains from the ground up, ensuring seamless code delivery to production. From orchestrating cloud-based solutions to creating robust automation processes, I am up for any challenge!
Currently, I am actively seeking fully-remote DevOps/Python developer roles within EMEA or APAC time zones. Beyond my technical acumen, I have a keen interest in natural resources investing and stay active with Thai boxing.
If you are seeking a versatile professional to elevate your team’s SaaS initiatives, I would be delighted to connect and explore new opportunities with you. Looking forward to collaborating on exciting projects ahead!
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
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, Savitzky–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
– 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
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
– 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)
– 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
I’m a data scientist with a Ph.D. in Cognitive Psychology and a graduate minor in Computer Science.
I am a results-driven full-stack developer with a Bachelor’s degree in Electronic and Electrical Engineering and over 5 years of professional experience. My expertise lies in utilizing cutting-edge technologies such as Node.js, React, AWS, CircleCI, and databases like MongoDB, MySQL, and Postgresql.
Technically sophisticated professional with extensive experience leading IT teams, project management, cybersecurity program development, business innovation, and systems virtualization. Expert in developing innovative solutions and secure technology plans that provide value, align with business objectives, and follow industry best practices.
Dedicated IT professional with a solid foundation in Desktop Support Level II, seeking to transition into an entry-level cybersecurity role. I bring a robust set of transferable skills, including technical troubleshooting, networking knowledge, vulnerability assessment, and a keen understanding of user behavior.
Resourceful Engineering Program professional with a strong emphasis on cloud security and integration. Proven experience in building and nurturing stakeholder relationships, leading diverse projects, and driving solutions that exceed client expectations.
