My name is Tal and I am a data scientist at the Starbucks Global Center of Excellence, where I conduct pricing analysis projects and run experiments to assist Starbucks’ global markets with launching new products, testing store changes, or handling evolving macroeconomic conditions. My previous roles as a data science analyst at Accenture Research and research analyst at the Philadelphia Fed built up my data, research, and economic analysis skills that I now employ as a data scientist. Outside of work, I enjoy running and exploring museums around NYC, where I currently live.

The essential skill for any successful data scientist is curiosity and an analytical mindset to explore questions you have about the world. In any role or company, data is messy and can be examined and broken down in a myriad of ways - it is up to you to ask questions and learn the data deeply and figure out how to appropriately analyze and summarize findings. Of course, most of this exploration is done in a programming language, typically Python or SQL (both of which I use daily). Although classes and on-the-job experience helped me learn these languages, much of it was self-taught through data science projects I have published on my website: https://www.visualizecuriosity.com/

Practice, practice, practice. Your talent as a data scientist will be directly proportional to the hours you put in working with data, coding, creating visualizations and write-ups on your findings and results. You will most likely constantly struggle to figure out how to accomplish an analysis or resolve an error at first, but only by repeatedly facing these obstacles and learning how to work through them will you improve. Pursue side projects, like publishing data science projects on your personal website or using data in volunteering capacities (like our breaking into data science article up on Menti HERE!) will give you a useful structure to practice within!

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OpenAI recently unveiled “Deep Research,” an AI tool capable of conducting complex internet research and generating detailed reports in minutes. Demonstrated on Youtube, this tool follows the release of another AI that handles online grocery shopping and book reservations.

Deep Research, available through ChatGPT Pro for $200/month, can perform tasks ranging from ordering food to synthesizing diverse information across the web. Despite potential inaccuracies, known as “hallucinations,” and challenges in discerning reliable information, it offers significant benefits for fields like finance, science, and law. Read more HERE from the New York Times.

Alphabet, the parent company of Google, reported quarterly revenue of $96.5 billion, slightly missing Wall Street’s forecast due to weak cloud computing sales, which are crucial to its AI expansion strategy. Despite a 28% profit increase to $26.5 billion, concerns rose about Google Cloud’s performance against rivals like Amazon and Microsoft. Alphabet plans to increase capital expenditures to $75 billion in 2025, aiming to enhance AI capabilities despite the rising popularity of competitors like DeepSeek. Read more HERE from the New York Times.

Amazon’s Candid Chats program is an excellent resource for students navigating the interview process, offering an informal, optional conversation with an affinity group ally or member during the final interview stage.

This 30-minute virtual chat provides candidates with a unique opportunity to ask questions about Amazon’s culture, career growth, and work-life balance without the pressure of it impacting the hiring decision. Feedback indicates that these chats often help candidates feel more confident about accepting job offers, as they provide insights into the company from an employee’s perspective, separate from the recruitment team. See more of their content HERE!