Data Scientist
4 weeks ago
We are seeking an experienced Data Scientist with expertise in Large Language Models (LLMs) and financial data modeling. The ideal candidate will combine strong ML/AI capabilities with deep understanding of financial markets and FinTech applications, capable of developing and deploying sophisticated language models and financial prediction systems.
Key Responsibilities
- Design and implement LLM-based solutions using frameworks like LangChain, handling everything from model training to production deployment
- Develop and optimize open-source LLM models for financial applications
- Create and maintain CI/CD pipelines for ML models, ensuring reliable model deployment and monitoring
- Build and deploy financial prediction models using market data, transaction data, and alternative data sources
- Implement risk assessment and fraud detection models for financial services
- Design and maintain data pipelines for real-time financial data processing
- Collaborate with FinTech product teams to integrate ML solutions into customer-facing applications
- Ensure ML systems comply with financial regulations and security requirements
Required Qualifications
- Master's degree or higher in Data Science, Machine Learning, Computer Science, or related field
- 4+ years of professional experience in data science with focus on FinTech or financial services
- Demonstrated experience with:
- LangChain and open-source LLM development
- Model training, fine-tuning, and deployment pipelines
- CI/CD practices for machine learning models
- Financial data modeling and analysis
- Strong programming skills in Python, with expertise in ML frameworks (PyTorch, TensorFlow)
- Proficiency in SQL and experience with financial databases
- Experience with cloud platforms (AWS, GCP, or Azure) for model deployment
Preferred Qualifications
- Experience with specific LLM frameworks (Hugging Face, OpenAI API)
- Knowledge of quantitative finance and financial markets
- Experience with financial regulations (GDPR, CCPA, FINRA requirements)
- Background in developing trading algorithms or risk models
- Familiarity with blockchain and cryptocurrency technologies
- Experience with real-time data processing systems
Required Skills
- Deep Learning: Expertise in training and fine-tuning large language models
- Financial Analysis: Understanding of financial markets, instruments, and indicators
- DevOps: Experience with ML model deployment and monitoring
- Problem-solving: Ability to develop innovative solutions for complex financial problems
- Communication: Excellence in explaining technical concepts to stakeholders
Technical Stack
- LLM Frameworks: LangChain, Hugging Face, open-source LLMs
- ML Tools: PyTorch, TensorFlow, scikit-learn
- Cloud Services: AWS SageMaker, Azure ML, or similar
- DevOps: Git, Docker, Kubernetes
- Monitoring: MLflow, Weights & Biases
- Financial Data: Bloomberg, Reuters, or similar financial data providers
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