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Sr Data Scientist
  • Python
  • Spark
  • SQL
  • Java
  • SAS
  • Tableau
  • Data Visualization
  • Hadoop
  • SPSS
  • QlikView
  • Product Analytics
Atlanta, GA
149 days ago

The TSYS Issuing segments has one of the richest datasets on the planet, as we process credit card transactions for over 130 global banks, with nearly 800 million accounts on file and close to 30 billion transactions a year. You will help build analytical products that enhance the value and efficiency of this financial system. As a member of the Research & Development team, the Data Scientist is responsible for experiments and constructing new product porotypes on existing and new research. Deploys data-driven exploratory analysis as well as predictive models to solve business problems across financial services industry, particularly in the area of Originations, Risk and Fraud, Digital engagement, Payments and Customer Management. Designs and analyzes experiments to test new product ideas and convert the results into actionable product recommendations. Leads Analytics Model development, validation and maintenance. Assists with data collection, cleaning, visualization, model building, training, testing, and presentations to build analytics capability and drive efficiencies in business areas across TSYS.

What Part Will You Play?

  • Designs experiments, perform hypothesis testing, and build various data models
  • Analyzes and mines both structured and unstructured data to drive product centric as well as user-centric insights.
  • Develops and tests analytical solutions to be leveraged by both internal and external clients. Crafts compelling stories; makes logical recommendations; drives informed actions.
  • Applies advanced statistical techniques to understand ecosystems, user behaviors, and long-term trends.
  • Leads and executes independent quantitative research projects, leveraging data from multiple sources
  • Creates insightful automated dashboards and data visualizations to track key business metrics, with initial emphasis on issuing business.
  • Uses best practices to understand the data and develop statistical, analytical techniques to build models that address business needs.
  • Not an exhaustive list; other duties as assigned.

What Are We Looking For in This Role?

Minimum Qualifications

  • Bachelor's Degree - Quantitative Analytics, Statistics, Mathematics, Data Science, or similar discipline
  • Minimum of two years of working experience as a data scientist in the payments industry OR a minimum of 3 years of working as a data scientist in banking/financial services OR 5 years of working as a data scientist in all other industries.
  • Typically Minimum 4 Years Relevant Exp
  • Demonstrated experience with sophisticated analytics tools and programming languages (e.g., SAS, SPSS, R, Python, SQL, HiveQL, Spark, Hadoop)
  • Proficiency with visualization platforms such as Tableau, Qlikview, PowerBI, D3, or JavaScript

Preferred Qualifications

  • Prefer experience with Product Analytics
  • Patents, published research, and/or conference presentations in the data science field. are a big plus.
  • Experience with building AWS cloud-native data science applications
  • Experience in productization of data science products
  • Masters in Data Science or a related quantitative field. PhD's are also valid, but need to have work experience similar to MS candidates.
  • Experiencing building and deploying real-time scoring models into production
  • Master's Degree - Quantitative Analytics, Statistics, Mathematics, Data Science, or similar discipline

What Are Our Desired Skills and Capabilities?

  • Skills / Knowledge - A seasoned, experienced professional with a full understanding of area of specialization; resolves a wide range of issues in creative ways. This job is the fully qualified, career-oriented, journey-level position.
  • Job Complexity - Works on problems of diverse scope where analysis of data requires evaluation of identifiable factors. Demonstrates good judgment in selecting methods and techniques for obtaining solutions. Networks with senior internal and external personnel in own area of expertise.
  • Supervision - Normally receives little instruction on day-to-day work, general instructions on new assignments.

Not Ready to Apply? Join Our Talent Community!!

US Applicants:
TSYS is an equal opportunity employer (EOE) committed to employing a diverse workforce and sustaining an inclusive culture.

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