Senior Associate Digital Product Analytics

At American Express, we know that with the right backing, people and businesses have the power to progress in incredible ways. Whether we're supporting our customers' financial confidence to move ahead, taking commerce to new heights, or encouraging people to explore the world, our colleagues are constantly redefining what's possible - and we're proud to back each other every step of the way.

When you join Team Amex, you become part of a diverse community of over 60,000 colleagues, all with a common goal to deliver an exceptional customer experience every day. Here, you'll learn and grow as we champion your meaningful career journey with programs, benefits, and flexibility to back you personally and professionally. Every colleague shares in the company's success.

Together, we'll win as a team, striving to uphold our company values and powerful backing promise to our customers, communities, and each other every day. An we'll do it with integrity and in an environment where everyone is seen, heard and feels like they truly belong.

Join #TeamAmex and let's lead the way together.

The core of our company is not just the products we offer, but the personal connections our customers have with our brand. You can create digital experiences -from payments to rewards to servicing -that keep us connected to our customers and serve them at every touchpoint. From digital servicing and lifestyle features to secure, frictionless payment options. You can make a meaningful difference in our customers lives and help set us apart in the industry. Find your place in digital product on #TeamAmex

Responsibilities:

• Conduct statistical and machine learning analyses on large scale data sets to understand trends, detect anomalies, and formulate predictive insights.
• Develop analytical models from existing and derived databases using machine learning algorithms
• Perform statistical and machine learning analysis by developing and maintaining efficient SQL and Python code.
• Prepare dashboards in Tableau, Excel, and Adobe Analytics to communicate model outputs, and research findings in a clear and effective manner through effective visualizations.
• Maintain and increase professional and technical knowledge through self-research and training.

Minimum Qualifications:

• Master's degree in a quantitative field such as statistics, computer science, mathematics, economics, or finance

• One year of hands-on experience in the areas of inferential statistics, machine learning, simulation, and predictive modeling, including proficiency with SQL, Excel, R, Python, statistical modeling, and machine learning software, such as Jupiter Notebook.

Preferred Knowledge, Skills, and Abilities:

• Mathematical/statistical skills including regression analysis (linear, logistic, parametric), forecasting models, factor/component analysis, decision trees, segmentation, and cluster analysis
• Knowledge of distributed data systems such as Hadoop and related technologies (Spark, Pig, Hive, etc.)
• Strong critical thinking and logical reasoning skills
• Strong verbal and written communication skills

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.

If the role you are applying for is designated as hybrid or onsite, you will be required to demonstrate that you have completed your primary COVID-19 vaccination series (i.e., 2 doses for Moderna/Pfizer and 1 dose for J&J) in order to work in or visit any of our offices. This requirement is subject to legally required accommodations.

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Employment eligibility to work with American Express in the U.S. is required as the company will not pursue visa sponsorship for these 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, protected veteran status, disability status, age, or any other status protected by law