Data Analyst II

Worldpay • Cincinnati, OH

1d

About The Position

Are you ready to write your next chapter? Make your mark at one of the biggest names in payments. We’re looking for a Data Analyst II to join our technology team and help us unleash the potential of every business. What you’ll own as the Data Analyst II We are seeking a talented and motivated Data Analyst to join our dynamic team. The ideal candidate will have the ability to collect, clean, analyze, and interpret large datasets to identify patterns, trends, and insights that inform business decisions. Additionally, they will present these findings in clear, actionable reports and visualizations to stakeholders, effectively communicating the meaning behind the data to drive strategic improvements within an organization

Requirements

• Technical skills: Need to be proficient in SQL and, optionally, programming languages like Python, R, and SQL as well as data visualization tools like Tableau & PowerBI. Should also be familiar with database management tools and be able to analyze and draw insights from data.
• Soft skills: Need to be able to communicate well, solve problems, and think critically. They should also be able to pay close attention to detail to ensure the data they work with is accurate.
• Domain knowledge: Domain knowledge can help data analysts get up to speed quickly and solve problems more effectively.
• Storytelling: Data analysts need to be able to understand context, know who they're speaking to, and present effectively.

Nice To Haves

• Statistical modeling, simulation, forecasting, and experimental design techniques
• Database architecture, warehousing, and large-scale distributed systems
• Supervised, unsupervised, and reinforcement machine learning algorithms
• Creating dashboards and reports

Responsibilities

• Data collection: Gathering data from various sources, such as surveys, databases, and web analytics
• Data cleaning: Removing errors, inconsistencies, and inaccuracies from data to ensure its integrity
• Data organization: Putting data into the proper formats for analysis
• Data analysis: Using statistical methods to analyze data and draw conclusions
• Data visualization: Creating visual representations of data, such as pie charts, area graphs, and spiral plots, to help others understand trends and correlations
• Communication: Presenting technical analyses to a wider audience, such as executives or stakeholders, in a way that can be used to make data-driven decisions
• Exploratory data analysis: Aggregating data to generate summaries, identifying distributions, and highlighting outliers
• Programming: Using programming languages like Python and R to handle large data sets and solve complex equations
• Critical thinking: Analyzing and dissecting complex data sets to identify patterns and derive insights that can drive business decisions

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 1,001-5,000 employees