23 дня назад
Finance AI Data Scientist
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Finance AI Data Scientist (Financial AI/NLP): Building user-facing financial data and knowledge algorithms for query understanding, information extraction, retrieval, ranking, and research workflows with an accent on large language models, financial NLP, and continuously evaluated production systems. Focus on designing training datasets and benchmarks, optimizing retrieval-augmented generation and financial ranking, and applying reinforcement learning, active learning, and expert feedback to improve cross-market model quality.
Location: Asia; onsite or remote depending on the business team
Company
Binance operates a global blockchain ecosystem offering cryptocurrency trading, financial services, payments, research, and Web3 products.
What you will do
- Identify and develop high-value financial data and knowledge algorithms for user-facing AI and equity research scenarios.
- Design, train, evaluate, and optimize systems for query understanding, document understanding, information extraction, entity linking, event detection, classification, deduplication, and quality scoring.
- Develop retrieval, relevance modeling, and ranking algorithms that balance relevance, timeliness, source authority, popularity, and content quality.
- Build datasets, labeling systems, and evaluation benchmarks covering market data, fundamentals, earnings reports, announcements, news, research reports, and investment research data.
- Collaborate with Financial AI Engineers to integrate algorithms into knowledge processing and retrieval pipelines and deploy them to production.
- Apply fine-tuning, reinforcement learning, preference optimization, active learning, semi-supervised learning, and expert feedback to improve financial data agents.
Requirements
- Experience developing algorithms for financial data, brokerage, trading platforms, research institutions, wealth management, or fintech.
- Experience with financial content extraction, entity linking, event detection, or quality evaluation.
- Experience with financial large-model post-training, reinforcement learning, knowledge graphs, multimodal document understanding, or data-agent optimization.
- Experience with active learning, weak supervision, human-feedback loops, or large-scale data labeling and evaluation systems.
- Experience with cross-market or cross-language model transfer, or independent evaluation and calibration across markets.
Culture & Benefits
- Work with a global, user-centric organization and a flat structure.
- Build fast-paced projects with autonomy in an innovative environment.
- Access career growth and continuous learning opportunities.
- Receive a competitive salary and company benefits.
- Work from home may be available depending on the nature of the business team.
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