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Data Scientist
Отличная позиция в быстрорастущем финтех-секторе с фокусом на R&D и новейшие технологии (GenAI). Компания предлагает хорошие бенефиты, включая опционы и безлимитный отпуск, однако гибридный график может подойти не всем.
Сложность вакансии
Роль требует сильной академической базы (MSc/PhD) и практического опыта от 2 до 4 лет. Особое внимание уделяется современным технологиям, таким как Agentic AI и LLM, что повышает порог входа.
Анализ зарплаты
Предлагаемая роль соответствует уровню Middle Data Scientist. В Лиссабоне рыночные зарплаты для таких специалистов обычно находятся в диапазоне 45,000–65,000 евро в год, в зависимости от глубины экспертизы в области LLM.
Сопроводительное письмо
I am writing to express my strong interest in the Data Scientist position at ComplyAdvantage. With a solid background in Python and modern machine learning frameworks, I am particularly drawn to your focus on Agentic AI and RAG architectures. My experience in developing data-driven solutions and my passion for R&D align perfectly with your mission to neutralize global financial crime through innovative technology.
In my previous roles, I have demonstrated a strong ability to translate complex data into actionable insights and high-impact prototypes. I am excited about the opportunity to contribute to your AI Enablement workstreams and collaborate with your Product and Engineering teams to scale AI-driven features. The prospect of working with petabyte-scale data and pioneering the use of LLMs at a company backed by top-tier investors like Andreessen Horowitz is incredibly motivating.
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Откликнитесь в complyadvantage уже сейчас
Присоединяйтесь к ComplyAdvantage, чтобы создавать передовые AI-решения для борьбы с финансовыми преступлениями в Лиссабоне!
Описание вакансии
Role Summary
As a Data Scientist at ComplyAdvantage, you will develop and refine data-driven solutions to detect and prevent financial crime globally. Your core focus is R&D and Strategic Initiatives, conducting forward-looking research in ML, NLP, and Agentic AI to create measurable business value. In addition to deep-dive R&D, you will provide advisory support to Product and Engineering teams. By investing in AI Enablement workstreams, you will empower these departments with the quantitative insights and frameworks necessary to scale high-impact, AI-driven features.
Key Responsibilities
- Advance R&D in GenAI and Agentic AI: Develop high-impact prototypes for financial crime detection, leveraging multi-agent systems and RAG architectures built on foundational LLM frameworks.
- Contribute to Core Solutions: Collaborate with Engineering and Product to integrate and optimise AI components and frameworks into existing and new product features, ensuring reliability, scalability, and ethical performance in production.
- Evaluate LLM-based Systems: Contribute to the development and implementation of robust evaluation methodologies for LLM and agentic AI based systems, tracking key metrics related to task completion, reasoning accuracy, tool effectiveness, and overall reliability.
- Evaluate Model Context Protocol (MCP) applications: Connect our AI systems with external data sources and tools and provide recommendations for engineering implementation
- Data Understanding: Develop a solid understanding of our existing data sources, identifying challenges and suggesting potential improvements.
- Data Analysis: Use exploratory data analysis and data mining techniques to identify actionable insights for product improvement, including patterns that can inform and refine agent behavior and prompt engineering strategies.
- Research & Innovation: Continuously research and evaluate emerging tools, technologies, and best practices in data science, especially within the rapidly evolving field of Agentic AI, to keep ComplyAdvantage at the forefront.
- Cross-Functional Collaboration: Engage effectively with multi-disciplinary teams to actively share best practices, expertise and inspire innovation to foster an AI-first culture across the organization.
- Visualization & Roadmapping: Provide clear data insights and visualizations that will act as a basis for new ideas to be integrated into our product roadmap.
Required Qualifications
- MSc or PhD in a numerate subject (e.g., Computer Science, Mathematics, Statistics, Physics) or equivalent practical experience in a data-intensive role.
- 2-4 years of professional experience in data science or a related field, with a demonstrated ability to contribute to impactful data-driven solutions.
- Proficiency in Python, including experience with core data science libraries (e.g., Pandas, NumPy, Scikit-learn).
- Hands-on experience with modern machine learning frameworks such as TensorFlow or PyTorch.
- Familiarity with the foundational concepts of agentic AI and large language models (LLMs). This can be professional or through personal research.
- Basic understanding of popular agentic AI frameworks (e.g., LangChain, Pydantic AI).
- Knowledge of general evaluation techniques for AI models and an eagerness to learn and apply methods specific to agentic systems.
- Ability to communicate complex technical concepts effectively to a variety of stakeholders.
- Strong passion for data and solving challenging real-world problems using algorithms.
Preferred Qualifications
- Prior experience contributing to the deployment and integration of machine learning models into production data pipelines.
- Exposure to Big Data platforms such as Spark.
- Experience with Natural Language Processing, Entity Resolution, Graph Theory, or Graph Machine Learning.
- Experience working with or evaluating multi-agent systems or complex AI workflows.
What Success Looks Like
- In 90 days: You have successfully onboarded, gaining a clear understanding of our data landscape and current AI frameworks. You are actively contributing to R&D experiments and have established collaborative working relationships with peers in Engineering and Product.
- In 6 months: You have delivered your first significant R&D prototype or technical evaluation. You have begun contributing to our AI Enablement workstreams, perhaps by authoring a technical blog post or internal guide that translates your research findings into actionable knowledge for the wider team.
- In 12 months: You have completed multiple R&D initiatives that have shaped our technical roadmap. You are recognized for empowering other teams through your advisory support and quantitative expertise, consistently providing the "AI-first" insights that help Engineering and Product teams scale high-impact features.
About Data Science at ComplyAdvantage:
The Data Science tribe discovers and proves out impactful solutions that leverage our Petabyte-scale data infrastructure to neutralise global financial crime. We are responsible for research and development work that drives the "art of the possible" within our product suite. At ComplyAdvantage, we mine the internet for critical data and use it to power a dynamic knowledge graph, which uncovers hidden networks of financial bad actors. From exploring real-time stream processing with Kafka to pioneering the use of the latest LLMs, our modern technology stack allows us to innovate and build prototypes for cutting-edge agentic AI and large-scale algorithmic solutions that empower our clients.
What’s in it for you?
- Equity as we want you to have a part of what we are building
- Private medical insurance designed to keep you ensuring peace of mind while you excel in your career
- Unlimited Time Off Policy- A work-life balance and focus on our well-being are critical to keeping us performing at our best
- We embrace a hybrid approach that requires employees to be in the office for two days a week. We strongly believe that this approach fosters collaboration and enables the building of meaningful relationships
- You will also get a new starter budget to kit out your home office
- Opportunity to work on innovative projects with smart-minded people keen to share their knowledge and continuously improve
- Annual learning budget (prorated based on start date) to drive your performance and career development
About us:
Our mission is to empower every business to eliminate financial crime.
By harnessing AI, a unified platform, and an extensive partner ecosystem, we help customers turn compliance into a catalyst for growth, operational resilience, and enduring regulatory trust.
More than 3,000 enterprises across 75 countries rely on our end-to-end platform and the world’s most comprehensive financial crime risk intelligence. With full-stack agentic automation, we help organizations automate up to 95% of KYC, AML, and sanctions reviews, cut onboarding times by 50%, reduce false positives by 70%, and handle 7x more work with the same staff.
ComplyAdvantage is headquartered in London and has global hubs in New York, Lisbon, Singapore, and Cluj-Napoca. It is backed by Balderton Capital, Index Ventures, Ontario Teachers’ Pension Plan, Goldman Sachs, and Andreessen Horowitz. Learn more about compliance re-engineered for the age of AI at complyadvantage.com.
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Навыки
- Python
- NumPy
- Pandas
- PyTorch
- Machine Learning
- LLM
- Scikit-learn
- Spark
- TensorFlow
- Generative AI
- LangChain
- Natural Language Processing
- Graph Theory
Возможные вопросы на собеседовании
Проверка понимания архитектур, упомянутых в описании вакансии.
Можете ли вы объяснить принципы работы RAG (Retrieval-Augmented Generation) и как бы вы оценили эффективность такой системы?
Вакансия ориентирована на Agentic AI.
В чем основные различия между стандартным использованием LLM и агентными системами (Agentic AI)? Какие фреймворки вы бы выбрали для реализации?
Работа предполагает взаимодействие с инженерами и продуктологами.
Расскажите о случае, когда вам нужно было объяснить сложную техническую концепцию нетехническому стейкхолдеру. Каков был результат?
Упоминается работа с большими данными и Spark.
Как вы подходите к обработке и анализу данных на масштабе петабайт? С какими основными трудностями вы сталкивались?
Оценка моделей — ключевая обязанность.
Какие метрики вы считаете наиболее важными при оценке точности рассуждений (reasoning accuracy) в LLM-системах?
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