Job Abstract

DESCRIPTION:

Duties: Turn data into insights to impact the strategy and direction of Wholesale Payments products. Develop approaches for understanding clients and their behavior to deliver custom insights for a continually improved payment experience. Invent ways to answer key business questions by leveraging existing data assets or creating new ones. Develop, plan and execute analytical projects as an individual contributor and in teams. Contribute to analytical insights in collaboration with product managers, end users, developers, and other stakeholders to integrate data discoveries and processes into operational capabilities. Deliver practical data insights to senior leadership. Articulate findings in presentations, discussions and visualizations. Develop and maintain subject matter expertise in the wide range domains in payments and liquidity to support a diverse set of products. Develop bank data into data assets and insert tactical and strategic product solutions into current-state systems.

QUALIFICATIONS:

Minimum education and experience required: Master’s degree in Statistics, Econometrics, Mathematics or related field of study plus 3 years of experience in the job offered or as Data Scientist, Business Intelligence Analysts or related occupation. The employer will alternatively accept a Bachelor’s degree in Statistics, Econometrics, Mathematics or related field of study plus 5 years of experience in the job offered or as Data Scientist, Business Intelligence Analysts or related occupation.

Skills Required: Requires experience in the following: querying and analyzing large quantities of data using SQL, MySQL, Hive, or Spark; Python for data wrangling and transformation; using business intelligence tools such as Tableau to develop data visualizations and dashboards; leading and managing data science projects; defining the analytical agenda for projects; framing business questions into and executing analytical plans; presenting findings to senior level stakeholders for decision making; using pivot tables, plotting graphs, visualizations, and numeric models in Excel; designing experiments using different data science methodologies, data sources, or elements to gauge the proxy solution of vague business problems; running statistical and hypothesis testing; building regression and classification models including logistic, decision tree, and clustering; conducting principal component analysis.

Job Location: 383 Madison Ave, New York, NY 10179. Telecommuting permitted up to 40% of the week.

Full-Time. Salary: $163,238 - $170,000 per year.