Analyst VCA Data Services Practice
Analyst VCA Data Services Practice
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Job Description
The ideal candidates are problem solvers equipped with strong analytical & quantitative skills suited to address key strategic needs for Visas clients including issuers acquirers and merchants.
Adept at creative and critical thinking they are able to deconstruct problems and transform insights into large scale stateoftheart solutions. Candidates must be quick learners with a strong sense of personal responsibility.
Responsibilities
- Develop and grow exceptional internal client relationships
- Develop and deploy analytical solutions and techniques within the organization and VCAs clients
including issuers acquirers and merchants. - Work with large volumes of data extract and manipulate large datasets using standard tools such as Hadoop EcosystemPython PySpark SAS Presto SQL etc.
- Handson skills in cleaning manipulating analyzing visualizing large data sets.
- Data Cleansing/Wrangling This involve parsing and aggregating messy incomplete and unstructured data sources to produce data sets that can be used in analytics/predictive modeling.
- Develop and validate advance data mining tools algorithms and other capabilities to solve business problem.
- Utilize Visas data and analytic capabilities technology and industry expertise to develop standardized and implement the consulting analytical solutions.
- Identify relevant market trends based on a deep analysis of payment industry Information. Interacting with several internal and external stakeholders for the strategic definition of analysis and initiatives.
- Continuously develop and present innovative ideas to improve current business practices within Visa.
This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 23 set days a week (determined by leadership/site) with a general guidepost of being in the office 50% or more of the time based on business needs.
Qualifications :
Basic Qualifications:
2 years of relevant work experience and a Bachelors degree OR 5 years of relevant work experience
Preferred Qualifications
3 or more years of work experience with a Bachelors Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters MBA JD MD)
BA/BS required Masters degree preferred (e.g.: Statistics Computer Science Engineering or related fields).
4 years of overall experience with a preferred minimum of 2 in Banking or Payments Industry.
Strong interest in the future of payments a must.
Experience in retail banking payments financial services and/or technology industries
Prior proven experience in Credit Risk or Fraud Prevention to manage and develop policies adhoc analysis or models.
Proven Handson experience in advanced analytics and statistical modeling including Linear Regression Logistic Regression Clustering methods (e.g. Kmeans) Classification methods (Decision Trees/Random Forest) among others.
Experience working with large volumes of data (Big Data) extracting cleaning and manipulating large datasets using standard tools such as Python/PySpark SQL Hadoop/Hive Presto SAS etc.
Knowledge of visualization tools such as Tableau or PowerBI.
Continuously develop and present innovative ideas based on data driven approach to improve current business practices within Visa more specifically within the Risk Practice.
Excellent project management organizational and presentational skills.
Strong teamwork relationship management and interpersonal skills.
Ability to multitask various projects while meeting required deadlines.
Fluency in English (spoken/written) Spanish is a plus
Additional Information :
Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race color religion sex national origin sexual orientation gender identity disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
