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Why you can actually get this job
The posting states 'Remote' with no geographic, work authorization, timezone, or language restrictions beyond English. The role is explicitly open to remote work with no office requirement, and the language requirement is 'English Upper-Intermediate'—a proficiency level, not a second language mandate. No jurisdictional barriers are imposed.
“Remote”
Physical presence — Explicitly states remote work with no physical presence requirement.
“Opportunity to work remotely”
Physical presence — Confirms remote work arrangement is available.
“English Upper-Intermediate”
Language — Specifies English proficiency level only; no additional language is required.
“Source-provided allowed countries: (none — worldwide)”
Geographic scope — No geographic restriction stated; posting is open globally.
“full-time”
Work authorization — Employment type is full-time employee (W-2 equivalent); however, no work authorization or visa sponsorship language is present to trigger exclusion. No 'US authorization required' or similar gate language appears.
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)
