Head of Data & AI

Role Description

We are looking for a highly motivated and results-driven Head of Data & AI 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 Engineering
  • Design and evolve a scalable, reliable, and maintainable data platform architecture
  • Oversee development of robust ETL/ELT pipelines and real-time data streaming systems
  • Establish engineering best practices, including code reviews, CI/CD, data contracts, and observability
  • Lead technology selection and resource planning across ClickHouse, Spark, and supporting infrastructure
  • Ensure data quality through monitoring, alerting, SLA ownership, and remediation processes
  • Manage infrastructure costs and drive optimization across storage, compute, and cloud resources
• Artificial Intelligence & Large Language Models
  • Define and develop the company's overall AI direction and roadmap, aligning initiatives with long-term business strategy
  • Ensure operational stability and observability of ML services
  • Define and drive LLM strategy, including identifying high-value use cases, evaluating model providers (OpenAI, Anthropic, open-source), and leading end-to-end implementation
  • Architect and oversee LLM-powered products, including RAG pipelines, AI agents, and intelligent automation workflows integrated into core business processes
  • Establish MLOps/LLMOps best practices, including model versioning, evaluation frameworks, prompt management, and drift/hallucination monitoring
  • Drive responsible AI governance, including bias detection, explainability (SHAP, LIME), fairness auditing, and compliance with emerging AI regulations
  • Evaluate and integrate vector databases (Pinecone, Weaviate, pgvector) and embedding strategies to power semantic search and knowledge retrieval
  • Champion AI-assisted development practices (e.g., GitHub Copilot, Cursor) and foster an AI-augmented engineering culture across data teams
• Data Analytics & Quant
  • Drive advanced analytics, strategy, and Quant development
  • Partner with stakeholders to translate complex business challenges into data-driven solutions
  • Define and own key metrics, dashboards, and reporting frameworks to support executive and board-level decision-making
  • Lead experimentation practices to validate business impact of models and initiatives
  • Mentor teams, setting technical standards and career development paths

Qualifications

• 7+ years of hands-on experience across Data Engineering, Data Science, Quant, Data Analytics, delivering end-to-end solutions
• 3+ years of managerial experience, leading data teams
• 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)
• Deep understanding of core ML algorithms: regression, gradient boosting, time series, etc.
• Practical experience with ML libraries and platforms (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch)
• Strong foundation in mathematical statistics, probability theory, and quantitative modeling
• Proficient in SQL and experience with analytical and OLAP databases
• English Upper-Intermediate

Nice to Have

• 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
• Practical experience with integration of LLM with corporate systems for internal users

Benefits

• 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)