Job summary
Are you passionate about leveraging AI to solve real-world business challenges? Looking for a talented Data Scientist to join a growing data science function focused on driving innovation through NLP, LLM, and generative AI.
Key skills required for this role
Data Scientist
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Data Scientist
Job description
Job Title: Data Scientist - NLP, LLMs & Generative AI
Are you passionate about leveraging AI to solve real-world business challenges? We're looking for a talented Data Scientist to join a growing and forward-thinking data science function focused on driving innovation through NLP, large language models (LLMs), and generative AI.
This is an exciting opportunity to be part of a newly established team, working closely with the Head of Data Science to shape the roadmap, scale AI-driven solutions, and unlock new opportunities across the business. If you're hands-on with Python, experienced in building NLP or LLM-based applications, and thrive in a collaborative, problem-solving environment-this role is for you.
What You'll Do:
Design and deploy AI-powered tools that streamline internal processes and drive growth
Apply advanced NLP, LLMs, and automation techniques to enhance workflows and insights
Identify AI use cases with cross-functional teams and deliver practical, impactful solutions
Experiment with emerging open-source LLMs and generative AI technologies for adoption
Develop RAG (Retrieval-Augmented Generation) pipelines for extracting insights from unstructured data (PDFs, images, emails, etc.)
Support proof-of-concept development and help scale successful solutions across the business
What We're Looking For:
Technical Expertise:
5+ years of hands-on experience with Python for machine learning and data science
Strong background in ML, NLP, and LLMs, including training/fine-tuning models (e.g., Transformers, encoder-decoder architectures)
Experience with open-source LLMs (e.g., LLaMA, Mistral, DeepSeek, Qwen, etc.)
Familiarity with Hugging Face Transformers and related NLP libraries
Experience building RAG pipelines with embedding models and vector search
Application Development:
Comfortable developing APIs using FastAPI or Flask
Experience with tools like Streamlit or Gradio for building interactive AI applications
Demonstrated ability to integrate LLMs into real-world applications
Infrastructure & Deployment:
Experience testing models on local GPU infrastructure
Knowledge of Python environment management and containerization (Docker is a plus)
Data & Version Control:
Proficient with Git for collaborative development
Ability to access and process structured and unstructured data (e.g., SQL, PDFs, images, emails, JSON) Share
manages this role
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