Senior Analyst - Data Science

Key Skills

Apache Hive, Big Data Technology, Data Mining, Microsoft Office suites, PySpark, Python Programming, Scikit-learn, SQL

Job Description

You Lead the Way. We’ve Got Your Back.

With the right backing, people and businesses have the power to progress in incredible ways. When you join Team Amex, you become part of a global and diverse community of colleagues with an unwavering commitment to back our customers, communities and each other. Here, you’ll learn and grow as we help you create a career journey that’s unique and meaningful to you with benefits, programs, and flexibility that support you personally and professionally.

At American Express, you’ll be recognized for your contributions, leadership, and impact—every colleague has the opportunity to share in the company’s success. Together, we’ll win as a team, striving to uphold our company values and powerful backing promise to provide the world’s best customer experience every day. And we’ll do it with the utmost integrity, and in an environment where everyone is seen, heard and feels like they belong.

Join Team Amex and let's lead the way together.

How we serve our customers is constantly evolving and is a challenge we gladly accept. Whether you’re finding new ways to prevent identity fraud or enabling customers to start a new business, you can work with one of the most valuable data sets in the world to identify insights and actions that can have a meaningful impact on our customers and our business. And, with opportunities to learn from leaders who have defined the course of our industry, you can grow your career and define your own path. Find your place in analytics on #TeamAmex.

How will you make an impact in this role?

Global Commercial Services (GCS) is the global leader in providing payments solutions for Small, Medium, and Large Enterprises. We are in the business of helping our clients get business done! Accelerating sales and driving profitable charge volume growth are critical for the success of the organization. The Sales Enablement team is instrumental in driving these objectives.

The Senior Analyst will play a critical role in supporting the development of growth and data-driven strategies to improve portfolio performance and drive execution, while working alongside senior leadership within GCS.

This position will support the development and implementation of analytical solutions, to provide consultative support to the GCS leadership team. The incumbent will also highlight trends, risks, and opportunities to enhance business decision-making processes, while working very closely with Sales, Marketing, and Global Commercial Analytics teams to drive growth in the sales organization.

Expectations:

• Strong Analytical Skills: Apply analytical thinking to diagnose business needs and to establish analytical hypothesis and solutions; Deliver sophisticated analyses independently; Have outstanding knowledge of Hive, SQL, and Python encompassing data manipulation and statistical modeling/data-mining techniques; Leverage predictive modeling to identify tactics for channel optimization of existing areas and conceptualise opportunities.
• Superb Communicator: Ability to drive alignment among customers and key partners; Ability to write compelling messages addressed to various audiences/levels within the organization
• Strategic Mentality: Self-motivated individual who can problem-solve and think critically, to develop concrete insights backed by data and analytics; Find opportunities to strengthen business performance
• Results Driven: High level of accountability and ability to address ambiguous challenges; adaptable to evolving priorities and rapid change
• Out of the Box Thinking: Challenge status quo, innovate, and harbor strong curiosity
• Multi-Disciplinary Leadership: Ability to lead multiple and sophisticated work streams, and to work across departmental boundaries and deliver a diverse set of initiatives that result in impactful outcomes

Minimum Qualifications:

• 2-4 years of relevant work experience
• Bachelor’s Degree in a quantitative field (e.g., Economics, Finance, Accounting, Statistics, Data Analytics, Engineering)
• Proficiency in analytical tools (e.g., Python, PySpark, Hive, SQL, scikit-learn etc.)
• Experience in Big Data environment, inclusive of data mining techniques. Hands-on analytics / ML experience and understanding of data processing. Ability to address performance issues and to manipulate both structured and unstructured data
• Proficiency in CRM tools, Salesforce, and statistical software programs
• Advanced knowledge of Microsoft Office Suite (Excel pivot, macros; PowerPoint)
• Proven track record of independently developing novel analytical solutions optimizing business processes
• Ability to cultivate relationships and partner with multiple collaborators, with superb interpersonal skills
• Ability to deliver results, work independently, and prioritize tasks
• Self-starter who thrives in an evolving, dynamic environment

Preferred Qualifications:

• Master's Degree in a quantitative discipline

Salary Range: $55,000.00 to $105,000.00 annually + bonus + benefits

The above represents the expected salary range for this job requisition. Ultimately, in determining your pay, we'll consider your location, experience, and other job-related factors.

Depending on factors such as business unit requirements, the nature of the position, cost and applicable laws, American Express may provide visa sponsorship for certain positions.

American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law.

We back our colleagues with the support they need to thrive, professionally and personally. That's why we have Amex Flex, our enterprise working model that provides greater flexibility to colleagues while ensuring we preserve the important aspects of our unique in-person culture. Depending on role and business needs, colleagues will either work onsite, in a hybrid model (combination of in-office and virtual days) or fully virtually.