Data Science Analyst

The Colleague Services (CS) organization within the Colleague Experience Group (also known as Human Resources) at American Express plays a critical role in providing the best-in-class services, capabilities, data, and insights that enable a great colleague experience. The organization builds and evolves crucial products and services to enable the Colleague Experience Group (CEG) and the business. The CS organization handles the ecosystem of CEG products, processes, platforms, applications, third party partners, colleague insights and reporting, and colleague-related risk, compliance, and governance.

We are seeking an analytically curious colleague with a strong quantitative foundation and a passion for using data to improve the colleague experience. In this role, you will turn complex colleague data into clear insights, reporting and recommendations that help leaders make informed strategic decisions.

You will work across a varied portfolio of enterprise-wide colleague data and analytics requests, executive reporting, dashboards and strategic initiatives. You will also contribute to the development of an analytical Centre of Excellence for CEG by identifying new approaches, improving ways of working and helping the team deliver high-quality, actionable insights at scale.

This is an opportunity to build broad experience across the analytical lifecycle, from understanding business questions and preparing data through to developing analysis, visualising findings and communicating a compelling story to technical and non-technical audiences.

• Bachelor’s or Master’s degree in Statistics, Economics, Mathematics, Engineering, Data Science or another relevant analytical discipline.

• One to two years of experience applying quantitative analysis, statistical methods or data visualisation to solve business problems in a complex organisation.

• Proficiency in manipulating, analysing and interpreting data using SQL, Python, R or equivalent analytical tools.

• Experience extracting and working with data from enterprise data platforms; familiarity with LUMI is essential.

• Understanding of core statistical and experimental concepts, including distributions, regression, confidence intervals, correlation, statistical significance, p-values and hypothesis testing.

• Experience developing reports, dashboards or visualisations using tools such as Tableau, Power BI or equivalent technologies.

• Experience in People Analytics or working with HR data is preferred.

• Strong analytical curiosity, attention to detail and the ability to work through ambiguous or complex business questions.

• Ability to manage multiple priorities and deliver high-quality work in a fast-paced environment.

• Strong written and verbal communication skills, with the ability to use data storytelling to make complex findings accessible to technical and non-technical audiences.

• A collaborative mindset and the ability to build effective relationships with colleagues and partners across different functions.

Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions.

• Gather, validate, clean and prepare data from multiple sources, applying appropriate quality checks before conducting exploratory analysis.

• Analyse complex colleague datasets to identify meaningful patterns, trends and opportunities, translating findings into actionable insights and recommendations.

• Develop and maintain high-quality dashboards, reports and visualisations that enable leaders and stakeholders to make informed, data-driven decisions.

• Translate complex analytical findings into clear, accessible and compelling stories for a broad range of audiences, including senior executives.

• Partner with cross-functional teams to understand business challenges, define analytical requirements and develop practical, data-driven solutions.

• Deliver analysis in response to Blue Box-wide colleague data requests and contribute to strategic initiatives requiring colleague data and insights.

• Contribute to the development of Colleague Data Office’s analytical Centre of Excellence by introducing innovative approaches, reusable analytical methods and more efficient ways of working.

• Support ad hoc analysis and special projects, demonstrating flexibility, sound judgement and adaptability in response to evolving business priorities.

• Apply appropriate controls and attention to detail when working with sensitive colleague data.