Data Scientist

• Lead complex R&D initiatives: drive research and innovation in LLMs, NLP, machine learning, and graph analytics, turning advanced techniques into production-grade solutions.
• Own the full data science lifecycle: from discovery, framing, and exploration to deployment, customer delivery, and long-term monitoring.
• Shape ambiguous challenges into well-defined problem statements and design practical, state-of-the-art solutions aligned with business and regulatory needs.
• Engage directly with customers and stakeholders: collaborate to co-design use cases, set success metrics, and ensure solutions are adopted, measurable, and impactful.
• Mentor and guide peers: elevate technical excellence, foster knowledge-sharing, and set best practices for experimentation, testing, and deployment.
• Prototype rapidly: explore new ideas and validate hypotheses quickly, while balancing innovation with scalability and maintainability.
• Ensure production success: design, implement, and optimize pipelines for data integration, validation, monitoring, and retraining to sustain long-term model performance.
• Communicate effectively: distill technical complexity into compelling business insights, helping stakeholders make informed decisions.
• Champion excellence in execution: enforce best practices in MLOps, DataOps, and software engineering to deliver reproducible, maintainable, and scalable solutions.
• Continuously improve tooling and processes that accelerate delivery, experimentation, and collaboration across the data science function.

Senior Data Scientist

Data Scientist – Risk Management