Senior Data Scientist

At Valtech, you'll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking, or building the next generation of customer experiences, your work will help transform industries.

The role:

As a Data Scientist, you are passionate about experience innovation and eager to push the boundaries of what's possible. You bring 5+ years of experience, a growth mindset, and a drive to make a lasting impact.

You will thrive in this role if you are:

• A curious problem solver who challenges the status quo
• A collaborator who values teamwork and knowledge-sharing
• Excited by the intersection of technology, creativity, and data
• Experienced in Agile methodologies and consulting (a plus)

Role responsibilities:

• Generative AI Innovation & Strategy
• Lead GenAI Initiatives: Spearhead the identification of business scenarios where Generative AI (LLMs, GANs, Diffusion models) can be effectively applied to create tangible value.
• R&D & Prototyping: Research, design, and prototype cutting-edge approaches, exploring existing scientific research to inform solution development.
• Feasibility Analysis: Evaluate the technical and economic feasibility of Generative AI solutions for real-world client use cases.
• Vision Shaping: Collaborate with Product Managers and stakeholders to shape a clear, forward-looking vision of AI technology and its practical applications.
• Technical Execution & Implementation
• End-to-End Development: Implement and validate AI solutions for diverse business challenges, writing production-ready code using best engineering practices.
• Optimization: Optimize deep learning models for production environments to ensure scalability and latency requirements are met.
• Cross-Functional Collaboration: Collaborate closely with the ML Engineering team throughout all stages of the lifecycle, from initial research to final implementation.
• Data Strategy: Oversee the data mining process, including data collection, cleansing, and exploratory analysis to support model training and fine-tuning.

Must have qualifications:

• Experience & Education
• Total Experience: Minimum of 4+ years in Data Science and Analytics.
• Specialized Experience: Minimum 3+ years focused specifically on developing generative models (LLMs, GANs, VAEs, Diffusion models) and Deep Learning.
• Education: Bachelor's or Master's Degree in Computer Science, Mathematics, Applied Statistics, or a related field.
• Technical Skills
• Core AI/ML: Expertise in Computer Vision and NLP, with specific experience handling multimodal data (images, text, audio).
• GenAI Stack: Familiarity with Gemini, OpenAI GPT-x, open-source LLMs (Llama, Mistral, etc.), and experience in fine-tuning models (PEFT, LoRA).
• Retrieval-Augmented Generation (RAG): Expertise in designing RAG architectures to ground LLM responses in proprietary data.
• Vector Databases: Proficiency with vector stores such as Pinecone, Milvus, Weaviate, or ChromaDB for efficient semantic search and retrieval.
• Prompt Engineering: Advanced skills in prompt optimization, chain-of-thought reasoning, and framework usage (e.g., LangChain, LlamaIndex).
• Programming: Strong programming skills in Python with proven ability to write clean, production-ready code.
• Frameworks: Proficiency with deep learning frameworks such as PyTorch or TensorFlow.
• Cloud: Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP).
• Soft Skills
• Communication: Excellent fluency in English (B2+ or higher) with the ability to explain complex technical concepts to non-technical audiences.
• Problem Solving: A strategic thinker capable of devising holistic solutions for complex customer issues.

Nice to have qualifications:

• Experience with MLOps tools (e.g., MLflow, Kubeflow) and practices for deploying and monitoring AI models.
• Responsible AI: Knowledge of AI ethics, bias detection, and safety guardrails (e.g., NeMo Guardrails) for deploying LLMs securely.
• API Development: Experience wrapping models in APIs using FastAPI or Flask for integration with frontend applications.
• Knowledge of Reinforcement Learning (RLHF) and self-supervised learning approaches.
• Experience with emerging Generative AI architectures.

If you do not meet all the listed qualifications or have gaps in your experience, we still encourage you to apply. At Valtech, we recognize that talent comes in many forms, and we value diverse perspectives and a willingness to learn.

Skills

GPT, Gemini, LLM, Llama, Mistral, PyTorch, Python, TensorFlow