About Me

As an Economics graduate with a keen interest in Environmental, Social, and Governance (ESG) factors, I've dedicated my career to understanding the intricate balance between economic growth and sustainable practices. My journey in financial technologies has been driven by a vision to integrate data analysis and science into the heart of climate-focused decision-making.

Leveraging a strong foundation in quantitative and statistical analysis, I've honed my Python scripting skills to not only interpret complex datasets but also to predict market trends with an added layer of climate and sustainability metrics. My work in portfolio optimization and management is underscored by a deep-seated ambition to demystify financial data, providing a holistic view of market dynamics through the lens of ESG and sustainable finance.

With a commitment to continual learning, I am expanding my technical expertise into the realms of web development – mastering HTML and CSS to communicate insights more dynamically, as evidenced by this very website. My ongoing projects in data analysis and quantitative modeling are a testament to an ever-evolving skill set, aimed at being at the forefront of tech-savvy solutions in the climate domain.

Above all, it's the intersection of ESG principles and quantitative data where I find my passion and purpose, striving to become a catalyst for change in an increasingly data-driven world.

Technical Skills

• Programming Languages: Python, R, HTML, CSS
• Tools & Technologies: TensorFlow, PyTorch, Scikit-Learn, SQL, Pandas, Numpy, BeautifulSoup, NLTK
• Data Analysis: Statistical Analysis, Time Series Analysis, Data Wrangling, Data Visualization (Power BI & Tableau)
• Machine Learning: Regression, Classification, Clustering, SVM, Neural Networks, NLP

Machine Learning & Deep Learning Aspirations

My current educational and professional endeavors are increasingly centered around Machine Learning (ML) and Deep Learning (DL) techniques. I am actively engaging in learning how these powerful tools can be harnessed to construct strategic, mathematical, and statistical models that drive informed decision-making. The intricate mechanics of ML and DL, from neural networks to predictive analytics, are not just academic pursuits but pathways to practical applications in portfolio management, market analysis, and beyond.

The versatility of these skills is what excites me the most. While my industry domain currently lies in the intersection of climate science and ESG, I am eager to extend my reach into various sectors. I believe that the principles of ML and DL have transformative potential across industries, and I am keen to explore opportunities that challenge and refine my abilities. Whether it is through optimizing energy consumption models or enhancing the precision of financial forecasts, I am committed to being at the vanguard of data-driven innovation.

Broadening Horizons

In this journey, I aim to not remain siloed within a specific sector. The versatility of data science beckons a professional trajectory that spans multiple industries. My goal is to become a multifaceted data scientist who not only contributes to the field of climate science but also imparts value wherever complex data and smart algorithms can be used to solve problems and generate insights. From healthcare analytics to technological advancements, I am on a quest to be a part of diverse projects that harness the power of ML and DL, thus continually expanding my skill set and industry knowledge.

Current Endeavors

• Working on a predictive model for financial markets using time series analysis.
• Developing a recommendation system as part of my capstone project.
• Building on the ESG sentiment analysis project I started at my time in the University of Westminster.

Interests

• AI and Machine Learning: Especially in the context of finance and Climate.
• Blockchain: Exploring its applications in secure transactions and smart contracts.
• Quantum Computing: Learning about its potential impact on data processing and cryptography.

Career Goals

I aim to lead innovative projects in data science that can drive strategic decisions in business. I am particularly interested in financial technology and its capacity to improve market efficiency and transparency.