Job Overview
Role: Analyst – Data Science Location: Bangalore Experience: Freshers (from institutes of global repute) Qualification: B.E / B.Tech / M.E / M.Tech / B.Sc / M.Sc (CS/IT/Maths) Key Skills: AI/ML, Python, SQL, GCP (Vertex AI), Big Data (PySpark), ML Model Development Lifecycle (MDLC), Jupyter, Airflow, JIRA, Rally, Confluence
Job Description
For the American Express Recruitment 2026 drive, the company is seeking an Analyst to join the Data Science product team. This role is a unique blend of Technical Data Science and AI Product Management. You will not only build ML models but also contribute to the long-term AI product strategy and roadmap. You will work with Google Cloud Platform (GCP) and Big Data tools to translate business requirements into technical solutions at American Express's Bangalore facility.
Roles and Responsibilities
- Product Strategy: Contributing to the defining and articulation of long-term AI product strategy and roadmaps with clearly defined business metrics.
- Backlog Management: Prioritizing and managing product backlogs using tools like JIRA and Rally.
- Model Development: Driving end-to-end ML/AI product developments, from feature selection to deployment.
- Lifecycle Management: Contributing to all product lifecycle processes including market research, roadmap development, and requirements finalization.
- Innovation: Creating POCs (Proof of Concepts) for best-in-class AI-ML innovative products with scaling potential.
- Collaboration: Collaborating with engineering and design teams to transform MVPs into production-grade capabilities.
Skills and Eligibility Criteria
Educational Background: Undergraduate or Master’s in Computer Science, Information Technology, or Mathematics from institutes of global repute.
Experience: Freshers.
Mandatory Technical Skills:
- Strong background in AI / ML with proficiency in Python and SQL.
- Knowledge of Google Cloud Platform (GCP), BigQuery, and Vertex AI.
- Familiarity with Big Data Platforms like Hadoop and PySpark.
- Understanding of the ML Model Development Lifecycle (MDLC), including decision trees and boosting algorithms.
Competencies:
- Tools & Frameworks: Knowledge of Notebook-based IDEs (Jupyter) and Airflow.
- Familiarity with product management tools like Rally, JIRA, and Confluence.
- Soft Skills: Strong quantitative and structured problem-solving skills with excellent communication abilities.