JPMorgan Data Scientist Associate -Payments - Analytics & Reporting 

Philippines, Cebu City 

894142829

Job responsibilities:

• Partner with various departments to develop insights and analytic solutions tailored to client needs.
• Perform in-depth analyses and construct statistical models to uncover trends and key drivers influencing product, sales, risk, and operational decisions.
• Design and enhance data visualizations using existing tools or by developing new ones, while improving business dashboards.
• Implement processes and develop tools to enhance/automate data access, extraction, and analysis efficiency.
• Cultivate and maintain relationships with internal teams to proactively identify and address business needs through analytics.
• Work with leaders to develop and maintain executive reporting that will measure operational performance for BAU processes and strategic initiatives.

Required qualifications, capabilities, and skills:

• Minimum of 4 years of experience in quantitative data analysis.
• B.S. or M.S. in a quantitative discipline, such as Statistics, Applied Mathematics, Engineering, or Computer Science
• Proficiency in SQL.
• Experience with data visualization and BI tools like Looker or Tableau.
• Excellent skills with Microsoft suite (Excel, PowerPoint, SharePoint)
• Ability to tackle ambiguously defined problems, devise creative solutions, and meet tight deadlines.
• Excellent communication and presentation skills, with the ability to translate data into actionable insights.
• A collaborative team player who thrives in working with teams across the company to achieve shared objectives and can be self-directed with the ability to multi-task and keep a strong attention to detail.
• Demonstrated ability to manage tight delivery timelines, calmness under pressure and adapt to unexpected circumstances - capable of navigating in dynamic and complex environment
• MUST be willing in Cebu or willing to relocate in Cebu

Preferred qualifications, capabilities, and skills:

• Preferred experience with statistical software or programming languages such as R or Python.
• Preferably within the payments industry.