Analyst-Data Science

At American Express, our culture is built on a 175-year history of innovation, shared At American Express, our culture is built on a 175-year history of innovation, shared and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. As part of Team Amex, youll experience this powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career.

Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express

Join Team Amex and lets lead the way together.

Business Overview:

Credit and Fraud Risk (CFR) team helps drive profitable business growth by reducing the risk of fraud and maintaining industry the lowest credit loss rates. It applies an array of tools and ever-evolving technology to detect and combat fraud, minimize the disruption of good spending and provide a world-class customer experience. The team leads efforts to leverage data and digital advancements to improve risk management as well as enable commerce and bring innovation.

A single decision can have many outcomes. And when that decision affects millions of cardmembers and merchants, it needs to be the right one. Thats where AiDa Product team comes in who is part of the Credit & Fraud Risk (CFR) Global Data Science (GDS) CoE. The product specializes in powering a seamless unified experience for its AI / ML users and responsibly leverage enterprise data assets to support critical decisions for the company.

As a part of this team, youll have the opportunity to work in one of the best talent of product owners and managers in the industry. You will solve real world business problems while getting exposure to the industrys top leaders in AI / ML product management, decision science and technology. If you are passionate in getting to know all areas of our business and can translate business needs into remarkable solutions that can impact millions, you should consider a career in Product teams.

Job Responsibilities:

.Contribute to defining and articulation of long-term AI product strategy and roadmap with clearly defined business metrics and outcomes.

.Solve complicated business problems by prioritization & ownership of products and solutions to meet business objectives.

.Prioritize and manage product backlogs, by balancing the requirements of partners and stakeholders. Evaluate prospective features in AI Products pipeline against changing requirements in the direction of AI adoptions.

.Contribute to all product lifecycle processes including market (external) research, competitive analysis, planning, positioning, roadmap development, requirements finalization and product development.

.Translate product roadmap into well-defined requirements and acceptance test criteria.

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.Contribute to ideation and launch of innovative ML/AI products and capabilities. Innovate ways to evangelize products to drive Amex wide user adoption

.(For Learn): Curate and Deliver technical trainings in AI, Cloud, Hive and Spark for beginners to advance level users

.Create POCs for best-in-class AI-ML innovative products with the potential to scale

Qualifications:

.Strong quantitative, analytical, and structured problem-solving skills.

.Strong technical background in AI / ML with background on python, SQL, data analytics and data visualization

.Familiarity with ML model development lifecycle (MDLC): feature selection and engineering, different ML model algorithm families - Decision Trees, Boosting algorithms, optimizations considerations for ML models, deployment and serving challenges

.Knowledge of Google Cloud Platform (GCP), Big Query, GCP AI / ML capabilities such as Vertex AI.

.Knowledge of Big Data Platforms such as Hadoop and PySpark.

.Knowledge of designing and building big data tools and frameworks

.Demonstrate creativity and self-sufficiency along with strong interpersonal/ collaborative skills and experience working in global teams

.Understanding of the various ML Model deployment systems and processes with a basic knowledge of various model regulatory and governance policies.

.Knowledge of Notebook based IDE for performing AI / ML tasks such as Jupyter and Airflow.

.Familiarity with product management tools such as Rally, JIRA, and Confluence

.Excellent verbal and written communications skills

.Undergraduate/masters in computer science / information technology / mathematics from institutes of global repute.