Analyst - Data Products and AI EnablementJob SummaryThe
Analyst - Data Products and AI Enablementis 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.
Major 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.
QualificationsRequired- 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.
Preferred- 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
Core ExpertisePython & SQL | AI/LLMs | RAG | Vector Search | Embeddings | Data Engineering | APIs & Microservices | AWS | AWS Bedrock |Snowflake | FastAPI | Document Intelligence | LangChain | Cloud-Native Development | Serverless Architecture |React | Docker | Git/CI/CD
The above statements describe the general nature and level of work performed. They are not intended to be an exhaustive list of all responsibilities, duties, and qualifications required.
Education:- Bachelor's degree in Computer Science or a closely-related discipline, or an equivalent combination of formal education and experience
"Visa sponsorship/support is based on business needs. We do not anticipate providing visa sponsorship/support for this position."The typical base pay range for this role is as follows:
- New York / New Jersey: $ 85-126K
- Non-New York / New Jersey: $ 85-123K
depending on job-related knowledge, skills, experience and location. This role may also be eligible for certain discretionary performance-based bonus and/or incentive compensation. Additionally, our Total Rewards program provides colleagues with a competitive benefits package (in accordance with the eligibility requirements and respective terms of each) that includes comprehensive health and wellness benefits, retirement plans, educational assistance and training programs, income replacement for qualified employees with disabilities, paid maternity and parental bonding leave, and paid vacation, sick days, and holidays. For more information on our Total Rewards package, please click the link below.
Our hybrid work schedule is four days on-site and work remotely one day per week.
