Data Science Team Lead at OREDATA, leading teams to resolve data science challenges in a hybrid environment. Joining a digital transformation firm with a strong collaborative culture.
About the role
- Applied Data Scientist designing and implementing AI-driven pipelines for Binance's blockchain products. Collaborating on complex systems to enhance market understanding and trading intelligence.
Responsibilities
- Design and implement production-grade LLM pipelines powering Binance AI Products and next-generation agentic trading features — including multi-step reasoning agents, tool-selection frameworks, and autonomous workflow execution across spot, perpetual, and on-chain markets
- Continuously improve agent capabilities in understanding, reasoning, tool selection, and action execution — optimizing simultaneously for intelligence, latency, and reliability under high-frequency trading constraints
- Build and maintain evaluation frameworks for reasoning model outputs in crypto contexts — covering market analysis accuracy, agent decision quality, hallucination detection, and adversarial robustness against prompt injection in financial workflows
- Apply test-time scaling techniques — chain-of-thought, self-consistency, process reward models — to push agent reasoning quality in ambiguous, fast-moving market conditions
- Architect AI system components with rigorous attention to inference latency, throughput, and cost efficiency — leveraging serving frameworks such as vLLM and TensorRT-LLM — in a zero-downtime, 24/7 trading environment
- Integrate on-chain data sources, wallet intelligence, and crypto market signals into LLM-powered analytical pipelines — building the data layer that makes Binance's agents genuinely crypto-native
- Partner with research scientists to translate experimental findings into production-grade agentic solutions with clear performance benchmarks
Requirements
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, Statistics, Mathematics, or related technical field
- 0–5 years of industry or research experience in applied ML or AI engineering
- Strong Python programming skills ; Equally important: demonstrated comfort with vibe coding — using AI-assisted development tools fluidly as core part of your workflow
- Demonstrated hands-on experience with LLMs — prompt engineering, post-training, or end-to-end LLM application development
- Familiarity with multi-agent system design — task decomposition, tool use via MCP, memory management, parallel agent execution, and inter-agent communication
- Strong analytical thinking and problem decomposition; comfortable operating under ambiguity in fast-moving environments
Benefits
- Competitive salary and company benefits
- Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Data Scientist analyzing claims data, optimizing processes and collaborating across departments at Allianz Spain. Utilizing statistical techniques and developing predictive models for operational efficiency.
Data Scientist enhancing merchandising and inventory performance using machine learning techniques at Nordstrom. Collaborating with teams to develop data - driven solutions for better customer experiences.
Clinical Data Manager supporting research projects and managing patient databases at Mass General Brigham. Interact with patients and maintain data integrity in clinical research.
Technical Lead in Data Science guiding analytical systems design and team mentorship for a finance technology company. Collaborating across engineering and research to drive innovation and data excellence.
Technical Lead in Data Science at Voleon, driving the design and implementation of analytical systems. Mentoring a growing team of data scientists while ensuring methodological rigor in finance applications.
Data Scientist developing analytical solutions for customer data transformation and supporting critical business decisions. Focus on quality and integrity of data through statistical models and analysis.
Junior Data Scientist developing demand forecasting models for Nestlé’s Supply Chain team. Collaborating with analysts and planners to improve forecasting tools and processes.
HCM Data and Process Analytics Lead at ABB building business intelligence for HCM solutions. Analyzing data to drive improvements in performance and data quality across the organization.
Data Scientist owning and delivering production - grade data pipelines at Simbe Robotics. Collaborating with Product Management, Engineering, and Commercial teams to surface insights from retail data.