Company Overview

The hiring organisation operates within the foreign exchange and financial technology industry, working with market data to improve analytical visibility into currency movements and trading conditions. Its data science activities focus on identifying unusual patterns, assessing market behaviour, and developing tools that support research, monitoring, and operational decision-making.

Role Summary

The Data Scientist will specialise in analysing FX market behaviour and identifying unusual patterns in currency prices, spreads, volatility, and related market data. The role combines anomaly detection, statistical learning, and data engineering to distinguish meaningful market events from data-quality issues or ordinary fluctuations.

The ideal candidate will be comfortable working with high-volume time-series data, developing analytical detection methods, and validating findings before presenting them to research, risk, or operations teams.

Key Responsibilities

• Analyse intraday and historical FX datasets to identify unusual movements, pricing inconsistencies, and changes in market behaviour.

• Develop anomaly detection models using statistical methods and machine learning techniques.

• Investigate patterns in spreads, volatility, price movements, and currency-pair relationships.

• Build data pipelines that identify missing observations, inconsistent timestamps, outliers, and other data-quality issues.

• Establish baselines for normal market behaviour and evaluate deviations under different market conditions.

• Distinguish potential market anomalies from recording errors, data-feed problems, and expected volatility.

• Backtest detection methods against historical market events and assess false-positive rates.

• Develop monitoring dashboards and analytical reports for relevant research and operational stakeholders.

• Collaborate with data engineers, quantitative analysts, and risk specialists to integrate validated detection methods into existing workflows.

• Document model assumptions, investigation results, and recommendations for improving data quality and analytical reliability.

Requirements and Qualifications

• Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related discipline.

• Experience in anomaly detection, statistical analysis, machine learning, or financial data science.

• Strong Python skills and familiarity with pandas, NumPy, scikit-learn, or similar analytical libraries.

• Understanding of time-series data, statistical distributions, outlier analysis, and model evaluation.

• Experience querying structured datasets using SQL.

• Familiarity with foreign exchange markets, intraday pricing, spreads, or financial-market data is an advantage.

• Knowledge of data visualisation, automated monitoring, and reproducible analytical workflows.

• Strong investigative reasoning, attention to detail, and written communication skills.

Benefits

• Fully remote working arrangement within Estonia.

• Opportunity to solve practical analytical challenges in international FX markets.

• Exposure to market data systems, anomaly detection, and financial analytics.

• Collaboration with data science, engineering, and risk professionals.

• Opportunities to deepen expertise in statistical learning and financial-market monitoring.

Application Instructions

Interested applicants should submit an up-to-date CV and cover letter through the official application channel provided by the hiring organisation. A relevant project, technical report, or code sample involving anomaly detection, time-series analysis, or financial data quality is welcome.

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