Data Scientist

Job summary

Are you passionate about leveraging AI to solve real-world business challenges? Looking for a talentedData Scientistto join a growing data science function focused on driving innovation through NLP, LLM, and generative AI.

Key skills required for this role

Data Scientist

Important

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 talentedData Scientistto 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:

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:

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:

Experience with tools like Streamlit or Gradio for building interactive AI applications

Demonstrated ability to integrate LLMs into real-world applications

Infrastructure & Deployment:

Knowledge of Python environment management and containerization (Docker is a plus)

Data & Version Control:

Ability to access and process structured and unstructured data (e.g., SQL, PDFs, images, emails, JSON) Share

manages this role

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