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Senior Data Scientist - job 2 of 4

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.

As part of our diverse tech team, you can architect, code and ship software that makes us an essential part of our customers’ digital lives.  Here, you can work alongside talented engineers in an open, supportive, inclusive environment where your voice is valued, and you make your own decisions on what tech to use to solve challenging problems.  Amex offers a range of opportunities to work with the latest technologies and encourages you to back the broader engineering community through open source.  And because we understand the importance of keeping your skill fresh and relevant, we give you dedicated time to invest in your professional development. Find your place in technology on #TeamAmex.  

Let’s share success.

Infrastructure Data & Analytics aims to establish and reinforce a culture of effective metrics, data-driven business processes, architecture simplification, and cost transparency. 

As the Data Science team in Global Infrastructure Product Services embarks on building and deploying advanced data science and machine learning (ML) models, we are looking for a senior data scientist to build, deploy and monitor models in production.  This is an individual contributor role with responsibilities ranging from hand-on coding, debugging, documentation to stakeholder management and presentations.

A successful data scientist knows that delivering on that promise takes foresight, planning and agility.  We are seeking data scientists who are not only technically adept, but also understand the importance of harnessing the power of data to streamline financial operations, enhance decision-making and improve business outcomes. 

This team is focused on developing and maintaining dynamic technology infrastructure cost allocation and production models. The financial forecasting models will help ensure that our technology spending is transparent, efficient, and properly aligned with our strategic objectives. The role requires a blend of technical prowess in data engineering, data science, MLOps, and an understanding of enterprise infrastructure components & their economics.

Let’s build on what you know.

If you are a pioneer in developing and continuously evolving data science models in production that drive and monitor infrastructure and cost consumption analysis, you'll find a fit in our Data Science team in Global Infrastructure Product Services. To succeed in this newly forming team, you’ll need to be comfortable navigating ambiguity to stand up solutions 0à1 while discovering and leveraging enterprise platforms and best practices.

Here’s just some of what you’ll do:

  • Design and build scalable solutions using AI and Machine Learning (Generative AI, Natural Language Processing, Reinforcement Learning, and Time Series predictions) in document understanding, financial forecasting, and optimizing infrastructure resource utilization.
  • Own the model building and refining from identifying business problems, hands-on coding to curate training dataset, analyze data & validate models to delivering production grade solutions at scale.
  • Drive high-level and detailed technical design conversations.
  • Own and deliver documentation and methods required for model review with the model governance teams.
  • Be responsible for health and quality of the code across the portfolio, including leadership over innovation, functional testing, and CI/CD tool integration
  • Work closely with stakeholders across Technology, Finance and business unit portfolio leaders to define scope, requirements and incorporate cost drivers, allocation methods, and infrastructure nuances
  • Ensure best practices are aligned with Enterprise Architecture and Decision Science COEs
  • Develop SQL queries, scripts and routines to automate data processing and enhance the model’s accuracy and efficiency
  • Generate insightful data visualization and reports to aid in decision-making
  • Lead training sessions and create comprehensive documentation to empower end users to leverage the cost model effectively
  • Provide technical mentorship to team members at junior levels
  • Function as an active member of an agile team

Are you up for the challenge?  Here’s what you should have:

  • Master’s degree in Data Science, Mathematics, Computer Science, Engineering, Information Systems, or related STEM fields
  • 3+ years full lifecycle product development and engineering leadership in highly available, highly scalable, and high throughput systems
  • Experience in deploying out-of-the box LLMs and Generative AI solutions including setting up Vector DBs, Graph-RAG and extensive testing of LLMs. Hands-on knowledge of Chain-of-Thoughts, Tree-of-Thoughts, Graph-of-Thoughts prompting strategies. Must demonstrate deep knowledge of testing frameworks for Generative AI
  • Demonstrated experience with knowledge graphs
  • Experience in building and owning data science solutions and pipelines within the MLOps ecosystem in Vertex AI
  • Hands-on expertise with handling distributed (multi-tiered) systems and automated testing – unit and performance testing
  • Demonstrated experience in building and deploying a diverse set of Machine Learning (GLM, GBM, Neural Networks), Time series forecasting models and NLP solutions at scale
  • Proficiency and Hands-on Experience with Git, CI/CD tools, Elasticsearch, and a solution in each category: Orchestration, Container, Model Serving, Observability, and Feature Store
  • Strong proficiency in programming with Python, Machine Learning libraries and APIs (TensorFlow, Keras, PyTorch, ScikitLearn, H20.ai, XGBoost)
  • Experience in data visualization and observability with a focus on real time serving and monitoring of time series data with alerts
  • Strong project management skills and effective stakeholder management skills, coupled with a continuous improvement mindset
  • Excellent presentation and communication skills, capable of explaining complex technical choices in simple terms to a diverse audience
  • Experience in Financial Services industry is preferred
  • Thorough understanding of enterprise infrastructure technologies (Compute, Storage, Network, Mainframe) to inform model development is preferred.

Salary Range: $90,000.00 to $165,000.00 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.

We back our colleagues and their loved ones with benefits and programs that support their holistic well-being. That means we prioritize their physical, financial, and mental health through each stage of life. Benefits include:

  • Competitive base salaries 
  • Bonus incentives 
  • 6% Company Match on retirement savings plan 
  • Free financial coaching and financial well-being support 
  • Comprehensive medical, dental, vision, life insurance, and disability benefits 
  • Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need 
  • 20+ weeks paid parental leave for all parents, regardless of gender, offered for pregnancy, adoption or surrogacy 
  • Free access to global on-site wellness centers staffed with nurses and doctors (depending on location) 
  • Free and confidential counseling support through our Healthy Minds program 
  • Career development and training opportunities

For a full list of Team Amex benefits, visit our Colleague Benefits Site.

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. American Express will consider for employment all qualified applicants, including those with arrest or conviction records, in accordance with the requirements of applicable state and local laws, including, but not limited to, the California Fair Chance Act, the Los Angeles County Fair Chance Ordinance for Employers, and the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance. For positions covered by federal and/or state banking regulations, American Express will comply with such regulations as it relates to the consideration of applicants with criminal convictions.

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.

US Job Seekers/Employees - Click here to view the “Know Your Rights” poster and the Pay Transparency Policy Statement.

If the links do not work, please copy and paste the following URLs in a new browser window: https://www.dol.gov/agencies/ofccp/posters to access the three posters.

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

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Average salary estimate

$127500 / YEARLY (est.)
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$90000K
$165000K

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What You Should Know About Senior Data Scientist, American Express

If you're the kind of person who thrives on data and loves to tackle complex problems, then joining American Express as a Senior Data Scientist is where you want to be! Located in the bustling heart of New York, this role puts you at the forefront of using advanced data science and machine learning to influence financial operations and improve business outcomes. At Amex, you'll work in a vibrant team atmosphere, where your contributions are not only recognized but celebrated. You'll dive deep into designing and deploying cutting-edge models that optimize infrastructure cost allocation while ensuring efficiency and transparency. It's all about taking the lead and making data-driven decisions that empower the entire organization. You'll wear many hats in this individual contributor role—coding, debugging, managing stakeholders, and guiding others—making it perfect for those who enjoy variety in their work. By collaborating with talented engineers and using the latest technologies, you'll have the chance to enhance your skill set while crafting impactful solutions that truly resonate with our customers’ needs. Plus, Amex is committed to your growth, offering ample opportunities for professional development. If you're ready to leverage your technical skills in a supportive and inclusive environment and share in a common mission of helping others, this exciting opportunity with Team Amex might just be your next big step. Join us, and let's lead the way together!

Frequently Asked Questions (FAQs) for Senior Data Scientist Role at American Express
What are the responsibilities of a Senior Data Scientist at American Express?

As a Senior Data Scientist at American Express, you will design and build scalable solutions using AI and Machine Learning for financial forecasting, optimize resource utilization, and develop dynamic models related to technology infrastructure. Your role encompasses coding, debugging, and stakeholder management, aiming to create transparency in technology spending and enhance strategic decision-making.

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What qualifications do I need to apply for the Senior Data Scientist position at American Express?

To qualify for the Senior Data Scientist role at American Express, you should have a Master’s degree in Data Science or a related STEM field, alongside 3+ years of experience in product development and engineering leadership. Familiarity with deploying advanced Machine Learning models, handling distributed systems, and proficiency in programming languages like Python are essential.

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How does American Express support the professional development of Senior Data Scientists?

American Express prioritizes the professional growth of its employees, offering dedicated time for skill development and providing access to career training opportunities. As a Senior Data Scientist, you’ll not only apply your expertise but also enhance your competencies through continuous learning within a supportive team environment.

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What technologies will I work with as a Senior Data Scientist at American Express?

In the Senior Data Scientist role at American Express, you will work with cutting-edge technologies including Generative AI, Natural Language Processing, and various Machine Learning frameworks. You'll also engage with tools for CI/CD, model serving, and data visualization, allowing you to develop impactful data models within a sophisticated technology infrastructure.

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Can you describe the work environment for a Senior Data Scientist at American Express?

The work environment for a Senior Data Scientist at American Express is vibrant and collaborative, emphasizing inclusivity and teamwork. You’ll be surrounded by a diverse group of talented professionals, and the culture promotes open communication, innovation, and shared success as you work towards delivering the best customer experiences together.

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Common Interview Questions for Senior Data Scientist
Can you explain a successful project you led as a Senior Data Scientist?

In your response, highlight a specific project with measurable outcomes, detailing your role in problem identification, model development, and implementation. Emphasize collaborative efforts, how you tackled challenges, and the project's impact on business decisions to showcase your leadership and technical capabilities.

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How do you approach developing Machine Learning models?

Start by discussing your methodology for problem definition, data acquisition, preprocessing, and feature engineering. Illustrate your experience with model selection and evaluation, emphasizing how you ensure model accuracy and efficiency. Share a specific example that reflects your strategic thinking and technical skills.

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What are the key performance indicators you consider for your models?

Discuss how you evaluate model performance through various metrics such as accuracy, precision, recall, and F1 Score, depending on the specific use case. Provide examples of how these metrics help guide your refinements and improvements within your data science projects.

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How do you ensure the integration of stakeholder feedback in your data science projects?

Illustrate how you facilitate regular communication with stakeholders, gather requirements, and incorporate their insights throughout the project lifecycle. Share examples of how you adapted your approach based on feedback to ensure alignment with business goals and maximize impact.

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What experience do you have with MLOps and deploying models in production?

Detail your knowledge in MLOps processes, focusing on lifecycle management, CI/CD practices, and monitoring deployed models. Share a specific example of how you deployed a model in production, including the tools and methodologies utilized to maintain performance and reliability.

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How do you stay updated with the latest trends in data science and machine learning?

Discuss various avenues you use to remain current, such as attending industry conferences, participating in online courses, following thought leaders on social media, and engaging with data science communities. Emphasize your commitment to lifelong learning and how this benefits your work.

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Can you describe a time you had to navigate ambiguity in a data science project?

Provide a specific scenario where you faced uncertainty, illustrating your problem-solving approach. Explain how you gathered information, formulated hypotheses, tested solutions, and adapted your strategies to succeed despite the challenges.

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What tools or programming languages do you prefer in data science projects?

Mention your preferred tools and languages, such as Python, R, TensorFlow, or specific tools for data visualization. Relate this to your projects, highlighting how your choices contributed to successful outcomes and allowed you to perform tasks efficiently.

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How do you handle challenges in data cleaning or preprocessing?

Discuss your strategies for identifying and addressing common data issues, such as missing values or outliers. Share a particular example where your cleaning process significantly impacted the model performance, demonstrating your attention to detail and analytical thinking.

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What strategies do you use for effective data visualization?

Explain your approach to visualizing complex data sets, focusing on how you tailor your visualizations to your audience's needs, using tools like Tableau or specific Python libraries. Describe your process for ensuring clarity and impact, with examples of visualizations that led to informed decision-making.

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American Express is a multinational financial services corporation and global leader in providing personal, small business, and corporate credit cards.

2262 jobs
MATCH
VIEW MATCH
BADGES
Badge Family FriendlyBadge Office VibesBadge Work&Life BalanceBadge Rapid Growth
CULTURE VALUES
Inclusive & Diverse
Empathetic
Collaboration over Competition
Growth & Learning
Transparent & Candid
BENEFITS & PERKS
Medical Insurance
Dental Insurance
Mental Health Resources
Life insurance
Disability Insurance
Child Care stipend
Employee Resource Groups
Learning & Development
FUNDING
DEPARTMENTS
SENIORITY LEVEL REQUIREMENT
TEAM SIZE
EMPLOYMENT TYPE
Full-time, hybrid
DATE POSTED
April 3, 2025

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