Senior NLP, LLM Data Scientist (Fintech)

TL;DR

Senior NLP, LLM Data Scientist (Fintech): Developing AI solutions for various business domains, including goal-setting, efficiency, and data-driven insights for strategy, with an accent on automating data sources for ML models and end-to-end ML model development. Focus on domain adaptation, fine-tuning large language models, and developing Python back-end services for model deployment.

Локация: Москва, возможна удаленная работа из РФ.

Salary: 300 000 — 450 000 ₽/мес на руки

Компания

Сбербанк — крупнейший банк в России, Центральной и Восточной Европе, один из ведущих международных финансовых институтов.

Что делать

• Automate data sources for ML models in collaboration with ML Engineer/Data Engineer.
• End-to-end development of ML models, from MVP to the target solution, using the bank's tech stack.
• Work on NLP tasks such as preprocessing, classification, summarization, NER, semantic search, and clustering.
• Perform domain adaptation and fine-tuning of Sber's large language model (GigaChat) using internal/synthetic data.
• Develop LLM Plugins, including multi-hop reasoning and API integration.
• Develop Python back-end services for model deployment in a production environment.

Требования

• Experience in developing NLP models (required) and recommendation systems (preferred).
• High proficiency in Python and SQL.
• Fluency in basic Python libraries, including pandas, NumPy, matplotlib, and seaborn.
• Experience with NLP libraries: Pymorphy2, NLTK, Gensim, spaCy, and RegExp.
• Industrial experience in developing, training, testing, deploying, and monitoring model quality.

Культура и преимущества

• Flexible work arrangements: remote, hybrid, or office-based options.
• Mortgage benefits and preferential lending terms for employees.
• Fitness centers in offices.
• Free SberPrime+ subscription.
• Discounts on products from partner companies such as Okko, Sber Market, and Delivery Club.
• Comprehensive health insurance (DMS) from day one and preferential insurance for family members.
• Corporate pension program.
• Training at the Company's expense, including online courses and access to the corporate university.