Title: Tectonostratigraphic analysis of the western Huincul High (Neuquén Basin). Implications for geometry, kinematics and mechanics of inversion systems.Conducted research and numerical modeling on the 3D geometric and kinematic evolution of the inverted Neuquén Basin in Argentina. By analysing seismic reflection data and well data, a self-developed Python model was created, offering valuable insights into the development of inversion systems. Additionally, the study highlighted investment opportunities for hydrocarbons and CCS.

- Electrical Network Forecasting System - Lead a subteam to build a strategic forecasting model(written in Python) to predict growth in demand on the full network topology and the associated increase in load flow (written in C++). This model is used by network operator multiple clients to inform reinforcement investment decisions costing up to $300,00 per annum. The model relies on a Microsoft SQL database, containerised (using Docker) and deployed on Azure Cloud with automated CI/CD and stress testing- Carbon Emission Loanbook Analysis - Led a team to develop a tool for assessing the carbon emissions of a bank's vehicle loan book. This tool is used by commercial banks to report to regulators. The backend is written in Python, with a React frontend, a Postgres database, and is deployed on Azure Cloud.

Integrated in multifaceted teams delivering client facing and R&D projects— Web3 UI/UX - In a remote team of 4 prototyped and brought to production a crypto escrow system managing wallets, transactions and auditing on TRC20, ERC20, BEP20 chains. Involved in all parts of the system; writing the Typescript backend & React frontend; setting up Redis caching and Postgres database with a GraphQL API interface layer; automatic deployment using Gitlab CI/CD & Docker. This system is currently being utilised by the company with 100 daily users.— Betting Arbitrage Solution - Leading a team of 5 to develop custom libraries and an infrastructure for predicting and betting on horse racing, leveraging machine learning and statistical capabilities. The system utilises LASSO Regression, LSTMs, Monte Carlo Simulation and Markov Chains. A big emphasis on rewriting as well as optimising code and formatting conceptual ideas of math- ematicians. Working with CTO and CEO to improve team productivity and future knowledge retention.— Automated Logistical Component Trading - Involved in early stages of the project, working closely with the client to gather requirements and provide specifications. Designed the infrastructure and microservices of a system to trade electronic components, using NLPs to parse emails to extract content and to link buyers and sellers for more business opportunity. The different services consist of Python backends, Elasticsearch and Postgres databases. The system has increased sales and lowered the company’s manhours employed by improving the effectiveness of the company’s workflow.

Working in a small team developing a Mapping Webplatform that specialises in visualising geological andhydrocarbon data— Mapping Webplatform - Working on functionality of the platform: automated Python scraper for finding and cleaning geological and oil & gas geospatial data (infrastructure, licence blocks, field data); and Postgres database creation, management and optimisation. Using QGIS to create maps and compiling reports on the current energy market conditions in areas e.g. Russia.

Responsible for researching the topic: Analysis of physical properties of mineral phases with changes of temperature at the lower mantle in Ultra Low Velocity Zones (ULVZs) — Numerical Modelling & Data Analysis - Designed and developed a Python codebase to easily generate theoretical ULVZs spatial maps depending on compositions and abundances of minerals under various thermal and pressure conditions. These were compared to measured world ULVZs spatial maps developing viable parameters and models for the creation of ULVZs. Using ParaView software to latter model partial melting situations as well as flow, consequently analysing the physical property changes.

Responsible for processing, interpreting and modelling seismic data for the purpose of oil exploration— Seismic Data Processing - Create 2D/3D land and marine seismic surveys from initial raw form (segd, segy) to fully migrated seismic images using SeisSpace, which were later used for explo- ration. Experimenting with unconventional methods: e.g. overlaying a 2D ’land grid’ over poorly acquired 2D marine seismic to add corrections and migrating CDPs to true geographical location.— Synthetic Modelling - Researching slip sweep and simultaneous sweep signals to find interference in signal caused by the two processes. Using MESA Expert to create synthetic traces from well data (e.g. density & sonic logs) from nearby wells to create theoretical horizons and structures.

- Assisting in the well boring operations