As a Data Analyst (FKA Global Data Analyst) at Bloomberg, I have had the incredible opportunity to immerse myself in the dynamic world of financial data and analytics. Throughout my tenure, I have honed my skills in gathering, analyzing, and interpreting complex datasets from diverse markets worldwide, and had the great privilege of being at the forefront of data-driven innovations, participating in numerous projects that have significantly impacted the financial industry.
One highlight of my tenure was the opportunity to participate in and win an APAC-wide company Hackathon, where I collaborated with a talented team and used Machine Learning to try to classify and differentiate between relevant and non-relevant M&A news sources. Leveraging our expertise in Python, we developed a solution that impressed the judges and earned us the top spot. This experience not only reinforced my problem-solving skills but also demonstrated my ability to thrive in a fast-paced and collaborative environment.
In addition to the Hackathon success, I collaborated in designing and building (with Python) robust data pipelines for specific financial products. These pipelines have enabled seamless and real-time access to crucial market information, empowering our clients to make informed decisions swiftly and confidently. From data extraction and transformation to loading and visualization, I ensured that the pipelines adhered to the highest standards of accuracy and efficiency.
Working as a Data Analyst at Bloomberg has allowed me to delve into a vast array of financial data from global markets. I not only had the opportunity to provide valuable insights to our clients but also collaborated with cross-functional teams to enhance existing data products and create new ones. My interest in data-driven solutions and commitment to accuracy have allowed me to contribute meaningfully to the global financial landscape, but most importantly, learn about how to build better software!