Forward Deployed Senior Data Scientist

About the role

This position is focused on designing, developing, and deploying advanced data‑science and AI solutions for complex business challenges. Working directly with customers and fast‑paced delivery teams, you will translate needs into scalable, production‑ready models that drive measurable impact.

Key responsibilities

• Transform business problems into data‑driven solutions by exploring data, engineering features, and building predictive models.
• Design, train, evaluate, and optimise machine‑learning models for forecasting, classification, clustering, recommendation, anomaly detection, and causal analysis.
• Develop Generative AI applications using Large Language Models, Retrieval‑Augmented Generation, embeddings, vector databases, and agentic AI frameworks.
• Integrate AI solutions into enterprise applications, ensuring scalability, robustness, and production readiness.
• Define evaluation metrics, monitor deployed models, and continuously improve accuracy and reliability.
• Collaborate closely with customer teams, AI engineers, data engineers, product managers, and UX designers to co‑create end‑to‑end AI products.
• Communicate findings, technical trade‑offs, and recommendations clearly to both technical and business stakeholders.

Required profile

• Strong hands‑on expertise in data science, machine learning, and applied AI.
• Excellent proficiency in Python and SQL.
• Experience with ML frameworks such as Scikit‑learn, TensorFlow, PyTorch, and XGBoost.
• Solid understanding of statistics, hypothesis testing, experimental design, model evaluation, and feature engineering.
• Proven track record developing predictive models, recommendation systems, forecasting, anomaly detection, and classification algorithms.
• Hands‑on experience with Large Language Models, prompt engineering, Retrieval‑Augmented Generation, embeddings, vector databases, and AI orchestration tools (e.g., LangGraph, LangChain, CrewAI, AutoGen).

Required skills

• Python
• SQL
• Scikit‑learn
• TensorFlow
• PyTorch
• XGBoost
• Large Language Models (LLMs)
• Prompt Engineering
• Retrieval‑Augmented Generation (RAG)
• Embeddings & vector databases
• LangGraph
• LangChain
• CrewAI
• AutoGen