89 applicants

Company

Original Job Post

Visa · 3 days ago

Senior Data Scientist

Atlanta, GA

Full-time

Hybrid

Senior Level

$123K/yr - $197K/yr

4+ years exp

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Comp. & Benefits

Insider Connection @Visa

Discover valuable connections within the company who might provide insights and potential referrals, giving your job application an inside edge.

Responsibilities

Communicate with clients to understand the challenges they face and convince them with data.

Extract and understand data to form an opinion on how to best help our clients and derive relevant insights.

Develop visualizations to make your complex analyses accessible to a broad audience.

Work with stakeholders throughout the organization to identify opportunities for leveraging Visa data to drive business solutions.

Mine and analyze data from company databases to drive optimization and improvement of product, marketing techniques and business strategies for Visa and its clients.

Assess the effectiveness and accuracy of new data sources and data gathering techniques.

Develop custom data models and algorithms to apply to data sets.

Use predictive modeling to increase and optimize customer experiences, revenue generation, data insights, advertising targeting and other business outcomes.

Develop processes and tools to monitor and analyze model performance and data accuracy.

Position reports to the Employer’s Atlanta, Georgia office and may allow for partial telecommuting.

Qualification

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Office SoftwareStatistical ModelingMachine LearningData MiningProgramming LanguagesData VisualizationProblem-SolvingCommunication

Required

Bachelor's degree in Statistics, Operations Research, Applied Mathematics, Economics, Data Science, Business Analytics, Computer Science, Engineering, or a related technical field and four years of experience in job offered or in a Senior Data Scientist related occupation.

Managing and organizing work in Office software such as Word, Excel, PowerPoint and/or Teams.

Building predictive and descriptive statistical models using machine learning tool kit, Jupyter notebooks, Python, and/or SAS.

Data mining and statistical modeling (e.g., regression modeling, clustering techniques, decision trees, etc.).

Analyzing large data sets using programming languages such as Python, R, SQL and/or Spark.

Generating and visualizing data-based insights in software such as Tableau.

Communicating data-driven insights and conveying actionable recommendations.