Senior Data Analyst

As a Senior Data Analyst at FIS Global, your primary responsibilities will include transforming data sets, conducting complex data analysis, utilizing statistical techniques for predictive modeling, collaborating with cross-functional teams, and presenting findings through data storytelling. Your insights will play a pivotal role in supporting strategic initiatives and driving business growth.

To apply for the Senior Data Analyst role at FIS Global, you should have a bachelor’s or master’s degree in data science, statistics, computer science, or economics. Additionally, at least 5 years of data analysis experience—preferably in fintech or financial services—is desired. Proficiency in SQL and experience with data visualization tools is also essential.

To prepare for your interview for the Senior Data Analyst position at FIS Global, it's vital to familiarize yourself with their data analytics processes, statistical modeling techniques, and the specific tools they use. Practice articulating how you've successfully utilized data to influence business decisions, and be ready to discuss your experience with data storytelling and collaboration across teams.

Senior Data Analysts at FIS Global commonly use SQL for database management and advanced analytics tools for statistical modeling and data visualization. Familiarity with Microsoft tools and programming software is highly advantageous, enabling effective analysis and presentation of complex data insights.

FIS Global promotes a collaborative and inclusive workplace culture. As a Senior Data Analyst, you'll be encouraged to innovate and contribute to team efforts. With a commitment to diversity, the team welcomes individuals from all backgrounds, fostering an environment where every voice matters.

Yes, FIS Global provides ample opportunities for professional growth and development. As a Senior Data Analyst, you'll be part of a forward-thinking company that values continuous learning and offers pathways for career advancement within the analytics team and beyond.

The salary for a Senior Data Analyst at FIS Global ranges from $84,720 to $142,320, depending on various factors, including skills, experience, and location. It's best to discuss salary expectations with your recruiter during the hiring process.

In data cleansing, I ensure the accuracy and consistency of datasets through systematic validation checks. This includes identifying and rectifying missing or anomalous data points, applying best practices for data governance, and utilizing automated tools where available for efficiency.

Certainly! I once developed a predictive model for customer retention in a fintech application. Utilizing historical customer data and behavioral analytics, I applied logistic regression to identify key factors influencing churn, which led to targeted engagement strategies that significantly improved retention rates.

I have experience using Tableau and Power BI for data visualization. I find these tools effective for creating meaningful visual reports that simplify complex data sets, making it easier for stakeholders to understand insights and recommendations.

I prioritize my tasks by assessing deadlines, project impact, and resource availability. I often use project management tools to track progress and allocate my time efficiently, while staying responsive to changes in project requirements as they arise.

I frequently utilize regression analysis and time series forecasting in my work. Regression helps understand relationships between variables, while time series forecasting is invaluable for predicting trends based on historical data.

I focus on data storytelling by emphasizing the significance of the insights in context. Using visual aids, such as charts and graphs, helps convey key messages more effectively, and I ensure to translate technical terminology into simpler concepts that everyone can grasp.

I ensure data quality by implementing rigorous checks during the data intake process, regularly reviewing data sets for inaccuracies, and collaborating with teams to establish ongoing data governance best practices that maintain data integrity.

In a previous role, my analysis revealed a noticeable drop in customer engagement. I presented my findings and recommendations to the leadership team, which resulted in the development of a marketing strategy aimed at improving user interaction by 30%.

I have worked extensively with large-scale databases, optimizing SQL queries for performance and efficiency. My experience includes database management and using ETL processes to integrate data from various sources into a unified analytical framework.

One challenging aspect is ensuring alignment between data analysis and business goals. It requires not only strong analytical skills but also the ability to understand business strategies and communicate effectively with diverse teams to deliver relevant insights.