Analyst, Data Science

About The Team

The Data Science and Analytics team focuses on International Customer Investment Optimization and Prospect Data Analytics. The team partners with marketing and LFOs to drive business by providing consultation on Return on Investment (ROI), Investment Utilization, Revenue Yield, and key performance metrics. Stakeholders include executive leadership, Enterprise Forecasting, Planning & Analysis, Investor Relations, Marketing, Risk, and BU CFO teams. The team's vision is to transform how data science drives sustainable, long-term growth by adopting next-generation technology, re-inventing forecasting, tracking, and analytical processes.

Key Responsibilities

• Deliver on forecasting & actualization of key Finance & Acquisition KPIs to enable agile decisions.
• Support American Express planning process with yearly & long-term forecasts for key metrics.
• Provide insights into welcome offers & incentive investments across international markets.
• Support on LTV, finance profitability models & enable optimization of marketing investments.
• Deliver analytical studies with actionable insights while engaging with partners.
• Design and deliver high-quality business insight suites, scalable solutions, and accurate scorecards.
• Work with cross-functional teams to identify opportunities, understand business processes, and propose new solutions.
• Adapt to emerging technology to develop well-executed concepts and coordinate with cross-functional teams on new solutions.
• Analyze the existing environment, derive opportunities, and recommend alternative solutions.
• Plan project deliverables, prioritize day-to-day tasks, create project documentation, design, and monitor business performance indicators.
• Attend ad-hoc requests for solution support without impacting quality or timeliness.

Requirements & Tech Stack

• Working knowledge of Python, MLS, PySpark, SQL, Hive, Google Cloud.
• Working knowledge of data visualization tools like Tableau and Power BI is an advantage.
• Hands-on with data mining, cleansing, extraction/transformation to enable analysis, interpretation, and insights.
• Hands-on in modelling, ML, statistics, and hypothesis testing techniques.

Qualifications

• Bachelor's degree in Statistics/Mathematics/Economics/Engineering with relevant experience.
• Preferred: Post-graduation in Statistics/Mathematics/Economics/Engineering/Management.
• Strong analytical skills combined with excellent presentation and interpersonal skills.