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Wallex is a FinTech company providing a secure cryptocurrency exchange platform and digital asset payment solutions.
With a vision to become a leading global FinTech enterprise, Wallex is recognized as one of the largest cryptocurrency exchange platforms in Iran, enabling the online trading of more than 130 cryptocurrencies.
We are looking for a sharp, innovative, and self-driven Senior Data Scientist (Blockchain) to join our team. This position goes beyond traditional data analysis and model development. We deal with complex, high-stakes challenges across blockchain operations, including hot-wallet liquidity management, wallet risk assessment, and on-chain analytics. If you enjoy breaking down ambiguous problems, applying advanced statistical and optimization techniques, and building data-driven systems that directly influence real-world financial operations, this role is built for you.
Responsibilities:
Own end-to-end data science projects — from problem decomposition and data exploration to model development, deployment, and continuous performance monitoring.
Optimize hot-wallet replenishment by building probabilistic withdrawal-demand forecasts and designing replenishment policies that balance liquidity availability, operational costs, and security exposure.
Develop wallet risk-scoring systems to screen deposits and withdrawals against sanctioned and frozen addresses, assess indirect exposure through transaction graphs, and support risk-based review decisions.
Build on-chain analytics infrastructure by establishing wallet registries, reconstructing balances and transaction flows, and reconciling blockchain data with internal records.
Turn models into actionable data products such as replenishment recommendations, wallet-screening services, and operational decision systems that integrate into daily workflows.
Validate and improve production systems through backtesting, baseline comparisons, shadow-mode testing, performance monitoring, and feedback-driven model refinement.
Collaborate with Blockchain Engineering, Treasury, Finance, Compliance, and Data Engineering to translate business and operational challenges into reliable, scalable solutions.
Requirements:
Minimum of 5+ years of experience in data science, applied machine learning, operations research, or a closely related quantitative field, with experience owning at least one production system end to end.
Advanced proficiency in Python and SQL for data processing, modeling, analysis, and working with large-scale data warehouses.
Strong background in probabilistic and quantile forecasting, intermittent and bursty demand, statistical evaluation, and inventory optimization.
Solid understanding of optimization techniques and inventory policies, including reorder-point and order-up-to strategies, with the ability to balance competing operational and risk objectives.
Experience with graph analytics, transaction networks, risk scoring, or entity resolution. Experience in fraud detection, AML, or payment networks is a strong advantage.
Ability to work with raw blockchain data and integrate on-chain information with internal data sources.
Strong problem-decomposition skills, with the ability to turn ambiguous, high-impact challenges into well-defined analytical problems and practical solutions.
Excellent communication skills, with the ability to explain assumptions, model limitations, and technical findings to both technical and non-technical stakeholders.
Experience with blockchain fundamentals, including EVM transactions, UTXO and account-based models, token standards, and wallet operations, is a plus.
Familiarity with ClickHouse, streaming data, blockchain indexers, stochastic optimization, or financial graph research is considered an advantage.
We build, not watch — This is where you belong!
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