Data Scientist

Key Responsibilities:

• Design, develop, and deploy machine learning models with a focus on generative AI (e.g., LLMs, diffusion models, GANs).
• Apply generative AI for use cases such as text generation, summarization, classification, synthetic data creation, and intelligent assistants.
• Collaborate with data engineers and ML engineers to build scalable pipelines.
• Lead experimentation and validation of new GenAI models and tools.
• Support prompt engineering and fine-tuning of foundation models where applicable.
• Ensure compliance with data privacy, security, and ethical AI standards.
• Present findings and models to stakeholders in clear, actionable formats.

Required Skills & Experience:

• 5+ years of experience as a Data Scientist or ML Engineer.
• Strong proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, Hugging Face Transformers, LangChain).
• Deep knowledge of foundational models, LLMs (GPT, Claude, LLaMA, Mistral, etc.), and associated tooling.
• Hands-on experience with fine-tuning or customizing generative AI models.
• Solid grounding in classical ML (supervised/unsupervised learning), statistics, and NLP.
• Familiarity with deploying models via REST APIs, Docker, and cloud services (e.g., AWS, Azure, GCP).
• Experience working with enterprise data in complex environments (structured/unstructured).
• Strong problem-solving skills and ability to communicate technical concepts to non-technical audiences.

Nice to Have:

• Experience with vector databases (e.g., FAISS, Pinecone, Weaviate).
• Familiarity with GenAI enterprise platforms (e.g., OpenAI, Azure OpenAI, Cohere, Anthropic).
• Experience in regulated industries (e.g., healthcare, finance, public sector).
• Knowledge of European data protection regulations (e.g., GDPR).