Applied Data Scientist (AI)

Location: Tel Aviv, Israel

Company

Builds AI-powered cognitive banking solutions that analyze real-time transactional data to help financial institutions anticipate customer needs and provide actionable financial guidance.

What you will do

• Frame analytical problems, review prior art, and assess available data to validate new ideas.
• Engineer features and design models for behavioural financial data using classical machine learning, deep learning, LLM pipelines, and agentic workflows.
• Prepare model specifications, evaluation evidence, and risk documentation for production in a regulated environment.
• Collaborate with Engineering to move solutions from proof of concept into live services and controlled roll-outs.
• Monitor model performance, drift, and business KPIs, iterating based on production results.

Requirements

• 2–3 years of hands-on Data Scientist experience in a product environment.
• Strong Python skills with Pandas, NumPy, scikit-learn, and PyTorch.
• Experience with tabular machine learning, feature engineering, gradient-boosted trees, and model evaluation.
• Hands-on experience building GenAI and LLM applications, including RAG, prompt engineering, and evaluation of LLM-based systems.
• Experience building agentic systems with tool use, multi-step workflows, and orchestration.
• Clear technical writing skills and the ability to explain models to non-technical audiences.

Nice to have

• FinTech or banking experience.
• Transformer model fine-tuning and production inference experience.
• Experience taking models into production, including monitoring and post-launch iteration.
• Experience with AWS or Azure.

Culture & Benefits

• Work on AI products used by major financial institutions and their customers across global markets.
• Collaborate closely with Product and Engineering throughout the model lifecycle.
• Balance analytical quality, production readiness, and time to market when selecting technical approaches.