Analyst, Advanced Data & Insights - job 3 of 4

As an Analyst in Advanced Data & Insights at Visa, you will focus on extracting, cleaning, and analyzing data to generate actionable insights that drive business value. Your role will include validating data quality, creating visualizations, and supporting internal stakeholders with analytical expertise.

For the Analyst, Advanced Data & Insights position at Visa, you need to have strong skills in data analysis tools like Excel, SQL, Python, and Tableau. A background in a corporate environment with experience in data-driven decision-making is preferred along with excellent communication skills. Knowledge of payment processing is a plus.

In the Analyst, Advanced Data & Insights role at Visa, you will utilize tools such as Python for coding, Tableau for data visualization, and SQL for database querying. Familiarity with Excel and MS Office applications is also essential to assist in data manipulation.

Working as an Analyst in Advanced Data & Insights at Visa involves a hybrid model, allowing for flexibility between in-office and remote work. You'll collaborate with diverse teams across Europe in a dynamic and fast-paced environment, driving innovative analytical solutions.

At Visa, an Analyst, Advanced Data & Insights can expect ample opportunities for career development, including training in advanced analytical techniques such as Machine Learning and participation in global projects that enhance your skill set and professional growth.

When approaching data extraction, I start by identifying the key databases and understand the types of data needed for analysis. I primarily use SQL for querying and extracting data efficiently, ensuring that I have a clear plan to meet the analytical objectives.

I emphasize the importance of data cleaning as a critical step in the data analysis process. My approach involves identifying anomalies and inconsistencies in the data, using Python or Excel functions for transformation and validation to ensure high data quality before analysis.

I have extensive experience using Tableau to create compelling and easy-to-understand visualizations. I focus on ensuring that my visualizations not only display data but also tell a story and convey insights clearly to stakeholders.

To ensure data reliability, I routinely perform validation checks throughout the data extraction and cleaning phases. I cross-check my findings against other benchmarks or datasets and collaborate with peers to confirm data integrity.

In a previous role, I analyzed performance data from multiple sources and identified trends that indicated declining customer engagement. I developed a report that highlighted these issues and proposed specific strategies to enhance customer interaction, which led to significant improvements.

Managing multiple projects requires prioritization and time management. I use tools like project management software to organize my tasks and timelines, allowing me to focus on critical deliverables and allocate time effectively across projects.

I start machine learning model development by clearly defining the problem statement and gathering relevant data. I then preprocess the data, select the right models based on the data characteristics, and iterate to optimize model performance through validation.

Collaboration is key in analytics. In my last job, I worked closely with marketing teams to understand their data needs. We held regular meetings to align on objectives and I delivered reports that helped them tailor strategies based on customer insights.

I stay updated with trends in the payments ecosystem by following industry publications, attending webinars, and participating in online forums. Networking with other professionals and engaging in continuous learning helps me stay informed about evolving technologies.

I am motivated by the challenge of transforming raw data into meaningful insights that can lead to actual business impact. The creativity involved in problem-solving and collaborating with teams to find solutions is incredibly rewarding to me.