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About the Role

This role involves leveraging data science and Generative AI techniques to drive business value, researching emerging AI trends, and developing both backend APIs and frontend interfaces for AI-powered applications.

Responsibilities

• Collaborate with business users to understand priorities and use cases, proposing and developing solutions using data science and/or Generative AI techniques.
• Research emerging AI/data science techniques and identify relevant ones for adoption.
• Perform data wrangling and analysis, including preprocessing, cleaning, and feature engineering.
• Support the daily operations and maintenance of deployed data science models and products.
• Develop backend APIs and services to support AI model deployment and integration.
• Build frontend interfaces and user experiences for AI-powered applications.
• Document changes to existing products.
• Review and implement fixes for reported security vulnerabilities.

Requirements

• Minimum of Bachelor’s Degree in Computer Science, Computer Engineering, Machine Learning / Data Science / AI or related disciplines.
• Ability to understand and apply a range of AI/ML techniques for regression and classification.
• Familiarity with popular Python packages (e.g., pandas, matplotlib, scikit-learn, XGBoost, NLTK, spaCy).
• Understanding of LLM concepts (e.g., context windows, embeddings, chunking, token management) and architectures (e.g., RAG).
• Experience with context engineering techniques and prompt optimization strategies.
• Proficiency in Git and SQL.
• Proficiency in Business Intelligence tools (e.g., Tableau, Qlik, MS PowerBI, Microstrategy).
• Proficiency in modern programming languages (e.g., TypeScript, C#).
• Experience in cloud platforms and services, preferably AWS.
• Experience with Docker/Kubernetes.
• Experience with web frameworks and full-stack development, including backend frameworks (e.g., FastAPI, Flask, Express.js) and RESTful API development, and frontend technologies (e.g., React, Vue.js, HTML/CSS, TypeScript).
• Experience with LLM frameworks (e.g., LangChain, LlamaIndex, Hugging Face Transformers).
• Knowledge of vector databases and embedding techniques (e.g., Pinecone, Chroma, FAISS).
• Understanding of AI agent frameworks and multi-agent systems.
• Strong presentation skills and ability to explain technical concepts clearly to a non-technical audience.
• Proficiency in statistical software tools (e.g., R, SAS).

Skills

• Data Science
• Generative AI
• AI/ML techniques
• Regression
• Classification
• Python
• pandas
• matplotlib
• scikit-learn
• XGBoost
• NLTK
• spaCy
• LLM concepts
• RAG
• Context engineering
• Prompt optimization
• Git
• SQL
• Business Intelligence tools
• Tableau
• Qlik
• MS PowerBI
• Microstrategy
• TypeScript
• C#
• AWS
• Docker
• Kubernetes
• Web frameworks
• Full-stack development
• Backend frameworks
• FastAPI
• Flask
• Express.js
• RESTful API development
• Frontend technologies
• React
• Vue.js
• HTML/CSS
• LLM frameworks
• LangChain
• LlamaIndex
• Hugging Face Transformers
• Vector databases
• Embedding techniques
• Pinecone
• Chroma
• FAISS
• AI agent frameworks
• Multi-agent systems
• Statistical software tools
• R
• SAS

Education Level

• Bachelor’s Degree in Computer Science, Computer Engineering, Machine Learning / Data Science / AI or related disciplines

Equal Opportunity

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