I
Data Scientist
Not specifiedFull-timeData ScienceFinancial Services
Support enterprise data, analytics, and AI automation by developing machine learning models, LLM-powered agents, and production data workflows.
Responsibilities
- Analyze and model structured and unstructured data using Python.
- Design, train, evaluate, deploy, and monitor machine learning models.
- Build and orchestrate LLM-based agents, RAG pipelines, prompts, and evaluation frameworks.
- Integrate models and agents with internal systems using MCP and workflow automation platforms.
- Write maintainable SQL for analysis, reporting, and data exploration.
- Collaborate with data engineers on production data flows, logging, alerting, and performance tuning.
- Develop internal tools and dashboards for data and AI access.
- Share analytical findings and assess emerging AI tools.
Requirements
- At least 3 years of experience as a Data Scientist, Machine Learning Engineer, or similar analytical professional.
- Strong Python programming skills and experience with pandas, NumPy, scikit-learn, PyTorch, or TensorFlow.
- Solid knowledge of statistics and machine learning, including feature engineering, model selection, validation, and result interpretation.
- Hands-on experience with LLMs and agentic AI, including prompt engineering, RAG, tool or function calling, and agent frameworks.
- Advanced SQL proficiency and experience with large-scale databases such as PostgreSQL, MSSQL, or Oracle.
- Experience supporting model training, inference, and evaluation pipelines in production.
Nice to have
- Background in finance, trading systems, or financial market data.
- Experience with MCP servers and clients.
- Experience with n8n, Airflow, or similar workflow orchestration platforms.
- Experience with data visualization and business intelligence tools.
- Exposure to real-time processing technologies such as Kafka or Spark Streaming.