Head of Data & AI

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

Requirements

• • 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

• 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)