Head of Data

We are looking for a highly motivated and results-driven Head of Data to join our team full-time. In this strategic role, you will shape the vision, architecture, and delivery frameworks for Data Engineering, Data Science, Quant, and Data Analytics, unifying these teams into a single, high-impact function. This is a key leadership position, guiding both technical and managerial directions for our data organization.

We drive fintech innovation through deep analytical expertise and a data-first, engineering-driven approach.

Key Responsibilities

Data & Quant Leadership

• Define and lead the strategy across Data Engineering, Data Science, Quant, and Data Analytics, focusing on high business impact
• Build and manage cross-functional teams, including quants, data scientists, engineers, and analysts
• Drive advanced analytics, ML strategy, feature engineering, and model development with a focus on responsible AI
• Collaborate with stakeholders to turn complex business challenges into data-driven solutions

Data Engineering Leadership

• Design and evolve a scalable, reliable, and maintainable data platform architecture
• Oversee development of robust ETL/ELT pipelines and real-time data streams
• Establish engineering best practices: code reviews, CI/CD, data contracts, observability
• Drive technology selection and resource planning for ClickHouse, Spark, and supporting infrastructure
• Ensure data quality through monitoring, alerting, SLA ownership, and remediation processes

People & Cross-Functional Leadership

• Communicate effectively across technical and non-technical teams to influence decisions
• Lead cross-team processes (e.g., grooming, design reviews, retrospectives)
• Mentor team members, create growth plans, and foster a culture of psychological safety, accountability, and innovation

AI & LLM Strategy

• Define and drive GenAI and LLM strategy: identify high-value use cases, evaluate model providers (OpenAI, Anthropic, open-source), and lead end-to-end implementation
• Architect and oversee LLM-powered products: RAG pipelines, AI agents, and intelligent automation workflows integrated into core business processes
• Lead adoption of agentic AI frameworks (LangChain, LlamaIndex, AutoGen) to build autonomous multi-step reasoning systems
• Establish MLOps and LLMOps best practices: model versioning, evaluation frameworks, prompt management, and monitoring for drift and hallucinations
• Drive responsible AI governance: bias detection, explainability (SHAP, LIME), fairness auditing, and compliance with emerging AI regulations
• Champion AI-assisted development workflows (GitHub Copilot, Cursor) and foster an AI-augmented engineering culture across data teams
• Evaluate and integrate vector databases (Pinecone, Weaviate, pgvector) and embedding strategies to power semantic search and knowledge retrieval
• Collaborate with product and engineering to productionize AI features with robust feedback loops, A/B testing, and continuous model improvement

Requirements

• 7+ years of hands-on experience across Data Science, Quant, Data Engineering, delivering end-to-end solutions
• 3+ years of managerial experience, leading data teams including quants and data scientists
• Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, Engineering, or a related field
• Strong programming skills in Python, with experience writing clean, production-grade code
• Solid understanding of software engineering best practices (CI/CD, testing, code reviews, clean architecture)
• Practical experience with ML libraries and platforms (e.g., scikit-learn, XGBoost, PySpark)
• Deep understanding of core ML algorithms: regression, gradient boosting, time series, etc.
• Strong foundation in mathematical statistics, probability theory, and quantitative modeling
• Hands-on experience with LLMs, prompt engineering, and building production-grade AI systems (RAG, agents, fine-tuning)
• Familiarity with LLMOps tooling: experiment tracking (MLflow, W&B), vector stores, evaluation frameworks (RAGAS, DeepEval)
• Proficient in SQL and experience with analytical and OLAP databases
• English Upper-Intermediate

Nice to Have

• Experience with ClickHouse or other OLAP databases
• Background in trading or fintech
• Experience analyzing and modeling time series or high-frequency data
• Familiarity with anti-fraud systems, risk modeling, or portfolio analytics

We offer

• 20 paid vacation days per year
• 10 paid sick leave days per year
• Public holidays according to current legislation
• Medical insurance
• Opportunity to work remotely
• Professional education budget
• Language learning budget
• Wellness budget (gym membership, sports gear and related expenses)