Hey There!
I’m Catalina Sanhueza, a dual degree candidate at Boston University in Data Science and Psychology with a Business Administration minor. With hands-on experience in data analysis, programming, and strategic problem-solving —I’m passionate about using technology to drive innovation.
Now, I’m eager to break into the tech industry and explore the transformative potential of AI to solve real-world challenges!
Let’s connect—I’d love to explore opportunities where I can grow and contribute as part of your team!
Driven by Data, Inspired by Innovation, Empowered to Make an Impact.
I aspire to bridge the gap between data and innovation, leveraging artificial intelligence to solve complex challenges and drive impactful business decisions. My goal is to create smarter, data-driven solutions that optimize processes, uncover growth opportunities, and enhance user experiences. By combining my technical expertise with a deep understanding of human behavior, I aim to deliver innovative strategies that not only meet business objectives but also foster long-term success in an ever-evolving technological landscape.
My Experience
As a member of the Boston University Consulting Group, I gained hands-on consulting experience through the StrategyLab and Casing programs. In StrategyLab, I collaborated with a team to develop a market-driven growth strategy for Venmo, focusing on increasing adoption of their credit card. This involved conducting in-depth market research, competitor analysis, and consumer behavior profiling to deliver actionable recommendations to a panel of industry experts. Simultaneously, I honed my analytical and problem-solving skills in the Casing Program by mastering case frameworks, quantitative analysis, and structured brainstorming techniques.
Consulting Background
In my time BUFC I conducted comprehensive research on companies within the materials and energy sectors, delivering actionable insights to senior analysts and contributing to investment decisions exceeding $100,000. I collaborated with team members to develop strategic investment approaches and evaluate risk management techniques across emerging industries, including Nuclear Energy, Lithium, Hydrogen Gas, and Solar Power. This experience honed my skills in market analysis, strategic planning, and decision-making in high-stakes investment scenarios.
Financial Experience
As some who advocates for more women in Tech I worked alongside Girls Who Code. I collaborated with a team of 30 to inspire and empower young girls to pursue careers in technology. I led engaging Python coding workshops and mentored around 50 participants, providing guidance on personal projects and fostering their growth in programming skills. Through this role, I supported the next generation of female technologists, helping to bridge the gender gap in tech.
Advocate for
Women in Tech
As a research assistant in the Health Equity & Addiction Lab and the AMP Lab at Boston University, I ensure the integrity and organization of critical datasets that fuel groundbreaking studies. At the Health Equity & Addiction Lab, I facilitate the collection and structuring of data to support equitable healthcare interventions. In the AMP Lab, I contribute to research on motivation and social processes by managing data collected through innovative mobile technologies. My dedication to precision and efficiency drives impactful research and prepares me to support data-driven innovation in the tech industry.
Driving Research Forward
What is my technical background?
I have a strong technical foundation in programming and data management, complemented by experience with a variety of development tools and platforms. My skills span areas like coding, data visualization, version control, and cloud technologies, enabling me to contribute to projects that require a combination of technical expertise and innovative problem-solving.
Simone, UX Designer, Brushed
Languages
Python, Javascript, Rust, Bash, Excel, CSS, SQL, and HTML
Technologies
Tableau, Redcap, Git, GitHub, Visual Studio Code, RedHat Openshift AI, Podman, and Google Colab
Libraries
Matplotlib, Plotly, Scikit-learn, Pandas, Numpy, Ndarray, Petgraph: Ryon, Serde, CSV,