The field of data science is growing fast as organizations rely on data to make decisions and solve problems. Most people already see the value in data science. The real challenge is figuring out where to begin.
In this interview, Dennise Cardona, M.A. ’23, talks with Pooja Laveti, M.P.S. ’23. They discuss Pooja’s journey from graduate student to data analyst. Pooja shares useful tips on becoming a data analyst. She talks about important tools and how hands-on learning helped her succeed.
Building Passion for Data-Driven Careers
Dennise Cardona, M.A. ’23:
The field of data science is evolving rapidly. How do you stay updated on this dynamic industry’s latest trends, technologies, and methodologies? Are there any favorite resources or communities that you recommend to fellow data science enthusiasts?
Pooja Laveti, M.P.S. ’23, Data Science:
You need passion for data to succeed in this field. Every organization treats its data as a form of wealth because it contains essential insights. The UMBC Data Science program taught me how to find insights using tools, techniques, and real-world examples. If you like working with data and want to learn how to use it wisely, this program gives you a solid start.
Accelerating the Path to Becoming a Data Analyst
Dennise:
What are you doing now? What is your current role? How are you using what you learned?
Pooja:
I completed my two-year program in just one and a half years by accelerating my coursework. Soon after, I focused on entering the data analyst field.
It was a tough job market. However, I focused on data science and stayed dedicated to my career. Because of this, I got a job as a Data Analyst I at Sheetz.
Applying Data Science Skills in Industry
Dennise:
What excites you most about this new role at Sheetz?
Pooja:
I now apply what I learned in the classroom to real-world data challenges. Sheetz operates in the United States. It collects data on customer behavior, food service, fuel use, and store performance.
My job lets me analyze data with tools like Tableau, SQL, and Teradata. This helps support decision-making in different departments.
How Data Science Programs Prepare Analysts for Success
Dennise:
How did the program prepare you to do that? What were your biggest takeaways?
Pooja:
Python and SQL were the most valuable skills I gained. Every assignment connected to real-world data scenarios. We worked with large datasets, built models, and practiced problem-solving that mirrored the challenges we now see in industry. This hands-on experience made the transition into the workplace much smoother.
Developing Problem-Solving Skills Through Real Projects
Dennise:
Can you share a challenging project that shaped how you approach data science?
Pooja:
One of my major projects involved YouTube video predictions. We used machine learning, Python, Apache Spark, and Hadoop to analyze trends and predict which videos would gain traction. This experience taught me how to look at data in different ways. It also helped me think more critically as a data analyst.
Building a Professional Network in Data Science
Dennise:
Networking is crucial in any field. How did you build your network at UMBC, and how has it helped you after graduation?
Pooja:
Before UMBC, I worked for Accenture with a background in computer science. At UMBC, I connected with faculty, classmates, and industry professionals. These connections helped me learn about opportunities. They also improved my technical skills and boosted my confidence in data analytics.
Understanding the Importance of Data Ethics
Dennise:
Data ethics is gaining prominence in the industry. How did UMBC address ethical considerations in data science?
Pooja:
Courses on legal issues and cybersecurity helped me deeply understand data protection. We learned how to handle confidential data safely and ethically. This is important in today’s data-driven industries where privacy and rules matter.
Strategies for Standing Out in a Competitive Job Market
Dennise:
The job market for data scientists can be competitive. What strategies helped you the most?
Pooja:
The main differences are strong technical skills and the ability to share insights. You can do this using tools like SQL, Python, Tableau, and Power BI. Employers want professionals who can not only analyze data but also present it clearly in dashboards and reports.
The Future of Data Science and Key Skills to Develop
Dennise:
Where do you see the future of data science heading, and what should upcoming graduates focus on?
Pooja:
The future is moving quickly toward advanced technologies and automation. Graduates should focus on staying current with tools like machine learning frameworks and cloud platforms. Continuous learning is key to staying competitive and becoming a strong data analyst.
Conclusion
If you want to be a data analyst, Pooja’s journey shows that passion, practical learning, and persistence are key. UMBC’s Data Science graduate program focuses on practical skills, real-world projects, and ethical responsibility. This can create job opportunities in many industries.
With the right training, people can turn their interest in data into a rewarding career. This career can offer growth for many years.
Learn more about UMBC’s Data Science graduate programs.