Gen AI Data Analyst

  • Washington D.C., DC
  • Posted 18 hours ago | Updated 18 hours ago

Overview

On Site
Depends on Experience
Full Time

Skills

Extract
Transform
Load
Data Analysis
Data Manipulation
Data Science
Data Visualization
Artificial Intelligence
Collaboration
Communication
Computer Science
Evaluation
Amazon Redshift
Amazon S3
Amazon SageMaker
Microsoft Power BI
Prompt Engineering
Lifecycle Management
Machine Learning (ML)
Machine Learning Operations (ML Ops)
Generative Artificial Intelligence (AI)
Knowledge Sharing
Large Language Models (LLMs)
Amazon Web Services
Dashboard
Finance
Financial Reporting
Soft Skills
Software Engineering
Sonnet
Tableau
Teamwork
Training
Financial Services
KPI
Python
Regulatory Compliance
Reporting
SQL
Vector Databases
Workflow

Job Details

Top 5 Technical Skills:

  1. GEN AI
  2. Python
  3. SQL
  4. AWS Data Services
  5. LLM
  6. ML
  7. Sagemaker

Top 3 Soft Skills:

  1. Confidence in Communication skills for Teamwork and sharing
  2. Stand alone to get work done, Independen

Job Description:
Experience:
8+ years overall in Software Engineering disciplines, preferably in the financial services industry
2-3 years of experience in AI/ML engineering roles
Strong programming skills in Python, SQL and experience with AWS.

Key Responsibilities:
Design, test, and refine prompts for large language models (LLMs) to support financial reporting, summarization, and client communication tools.
Analyze structured and unstructured financial data using Python and SQL, delivering insights through dashboards and reports.
Develop and maintain data pipelines and ETL workflows to support GenAI model training and evaluation.
Use AWS SageMaker to build, train, and deploy machine learning and GenAI models.
Collaborate with data scientists, analysts, and business stakeholders to align AI solutions with financial objectives.
Monitor model performance and iterate on prompt and model design to improve accuracy and relevance.
Document workflows, models, and prompt strategies for internal knowledge sharing and compliance

Required Qualifications:
2 3 years of experience in data analysis or machine learning roles.
Proficiency in Python and SQL for data manipulation and analysis.
Hands-on experience with major AWS services, particularly SageMaker, S3, Redshift, and Lambda.
Experience working with LLMs (Anthropic Claude, Sonnet) and prompt engineering techniques.
Strong understanding of financial data, KPIs, and reporting standards.
Excellent communication and collaboration skills.

Preferred Qualifications:
Experience in the finance or fintech industry.
Familiarity with vector databases (e.g., FAISS, Pinecone) and retrieval-augmented generation (RAG).
Exposure to data visualization tools (e.g., Power BI, Tableau).
Understanding of MLOps practices and model lifecycle management.
Education
B Bachelor s degree in Computer Science, Data Science, Finance, or a related field.
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