Analyst – Data Products and AI Enablement

MUFG•Jersey City, NJ

1d•$85,000 - $126,000•Hybrid

About The Position

The Analyst - Data Products and AI Enablement is an early-career engineering role within the Chief Data & AI Office focused on developing data pipelines, AI-powered applications, and cloud-based data services that support the bank’s business, operational, reporting and analytics priorities. The role works closely with senior AI and data engineers, data scientists, product teams, and business stakeholders to transform enterprise data into secure, scalable, and actionable AI and data solutions. The ideal candidate combines strong software engineering fundamentals with hands-on experience in Python, SQL, cloud platforms, APIs, data engineering, and generative AI, and is eager to apply these capabilities to complex banking use cases.

Requirements

1-3 years of experience in software engineering, data engineering, analytics, or technology-related roles.
Basic to intermediate proficiency in Python and SQL.
Exposure to cloud platforms, APIs, databases, data pipelines, or modern software development practices.
Foundational knowledge of AI, machine learning, data engineering, or analytics concepts.
Strong analytical, problem-solving, communication, and teamwork skills.

Nice To Haves

Exposure to Kafka, Airflow, Spark, Kubernetes, AWS, or similar technologies.
Experience gained through internships, academic projects, or professional work related to data and AI solutions.
Financial services experience is a plus

Responsibilities

Develop and maintain data pipelines, APIs, and microservices that ingest, transform, validate, and deliver structured and unstructured banking data.
Build and enhance AI-powered data solutions, including LLM applications, RAG pipelines, semantic search, document intelligence, embeddings, and AI-agent workflows.
Develop Python-based services using frameworks such as FastAPI and deploy solutions using cloud-native technologies including AWS Lambda, ECS, containers, and serverless platforms.
Build document-processing and intelligent automation solutions using technologies such as AWS Bedrock, Textract, Snowflake Cortex, and LLM APIs.
Develop data ingestion, transformation, chunking, embedding, indexing, and retrieval workflows for enterprise AI applications.
Build lightweight user interfaces and internal applications using React, Streamlit, or similar frameworks to make data and AI capabilities accessible to business users.