Senior Data Scientist

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October 12

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Silent Eight

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Artificial Intelligence • Compliance • Fintech

Silent Eight is a company specializing in artificial intelligence solutions designed to combat financial crime. Their flagship platform, Iris 6, uses advanced AI techniques to identify and manage anti-money laundering (AML) risks with speed and precision. With significant investments in research and development, Silent Eight processes billions of transactions annually, providing solutions such as automated alert adjudication, name screening, transaction screening, and continuous monitoring to detect and prevent illicit activities like money laundering and terrorist financing. Their mission is to eliminate the profits from financial crime through the fusion of human expertise and AI technology, aiming to reduce the staggering $2 trillion laundered globally each year.

51 - 200 employees

🤖 Artificial Intelligence

📋 Compliance

💳 Fintech

📋 Description

• 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.

🎯 Requirements

• Bachelor’s degree, Master or PhD in Data Science, Computer Science, Statistics, or related field. • 6+ years of hands-on experience delivering data science projects from research to production, ideally in mission-critical domains. • Proven expertise with LLMs and modern NLP frameworks (LangChain, LlamaIndex, OpenAI APIs, HuggingFace, etc.). • Strong foundation in machine learning, graph analytics, anomaly detection, and unstructured data workflows. • Advanced proficiency in Python and SQL with a track record of writing clean, modular, testable, and production-ready code. • Experience with large-scale data platforms (e.g., PySpark, BigQuery) and scalable ML deployments. • Solid knowledge of MLOps and DataOps, including CI/CD, monitoring, retraining, and reproducibility. • Comfortable in Linux, Git, Docker, and modern collaboration workflows. • Exceptional communication and stakeholder management skills: able to translate technical insights into business outcomes and influence at all levels. • Proven ability to drive measurable impact: balancing state-of-the-art research with practical, customer-driven implementation. • A mindset of ownership, flexibility, and resilience: you adapt quickly, handle ambiguity, and are committed to delivering results.

🏖️ Benefits

• Remote work flexibility • Paid Development Days • In-house training • Team building events