Company Overview

The organisation operates in a data-driven financial environment where quantitative analysis, disciplined risk assessment, and reliable modelling support informed business decisions. Its risk and analytics functions work with financial datasets, statistical techniques, and analytical tools to understand exposure, evaluate uncertainty, and improve the quality of risk-related decisions.

The organisation values analytical integrity, transparent assumptions, effective model validation, and a practical understanding of how quantitative outputs are used in business operations. It seeks a Quantitative Risk Analyst who can combine statistical knowledge, financial reasoning, and technical proficiency to investigate risk exposures and produce meaningful analytical insights.

The successful candidate will collaborate with risk specialists, finance professionals, data engineers, and business stakeholders to develop analytical approaches that support risk monitoring, scenario analysis, and decision-making. The working environment encourages accurate reporting, reproducible analysis, clear documentation, and continuous improvement in quantitative methods.

Role Summary

The Remote Quantitative Risk Analyst will develop and maintain quantitative analyses that help identify, measure, and explain financial and operational risk exposures. The role involves statistical modelling, financial data analysis, scenario testing, sensitivity analysis, and the preparation of reports that support risk oversight and business planning.

The successful candidate will use Python, SQL, statistical methods, and relevant analytical tools to examine historical data, assess changing risk patterns, and evaluate the potential effects of different market or business conditions. The position requires the ability to distinguish observed results from assumptions, understand the limitations of quantitative models, and communicate findings clearly to stakeholders.

Working remotely within Estonia, the analyst will contribute to the development of repeatable analytical workflows, investigate unusual movements in risk indicators, and support improvements in model documentation and data quality. The role is suited to a professional who enjoys solving complex analytical problems and applying quantitative techniques to practical financial risk questions.

Key Responsibilities

• Analyse financial and operational datasets to identify risk exposures, emerging patterns, concentration points, and changes in risk indicators.
• Develop, maintain, and improve quantitative models used for risk measurement, financial analysis, scenario testing, and decision support.
• Apply statistical methods to investigate relationships between variables, assess historical behaviour, and evaluate the reliability of analytical findings.
• Use Python, SQL, and relevant analytical libraries to collect, clean, transform, and analyse data from approved internal and external sources.
• Conduct sensitivity analysis to understand how changes in market variables, assumptions, portfolio characteristics, or business conditions may affect risk outcomes.
• Develop scenario analysis and stress-testing approaches to evaluate potential outcomes under adverse, unusual, or rapidly changing conditions.
• Analyse relevant financial risk measures, which may include volatility, exposure concentrations, drawdowns, expected losses, and other indicators appropriate to the business context.
• Support the development of quantitative frameworks for assessing market, credit, liquidity, counterparty, or operational risk where relevant to the organisation’s activities.
• Review historical risk events and investigate the factors that contributed to material changes in risk exposure or model output.
• Validate analytical datasets and model inputs to identify missing values, inconsistent records, outliers, and data-quality issues that could affect conclusions.
• Develop repeatable scripts, analytical templates, and automated workflows that improve the consistency and efficiency of risk reporting.
• Compare model outputs against historical observations, established benchmarks, or alternative analytical approaches to identify potential weaknesses.
• Assist with model validation by documenting methodologies, testing assumptions, examining performance, and identifying areas requiring further review.
• Monitor risk indicators and investigate unusual movements, unexpected results, or deviations from established thresholds.
• Work with finance and risk colleagues to translate business questions into clearly defined quantitative analyses.
• Prepare technical reports, visualisations, and concise summaries explaining risk movements, modelling assumptions, analytical limitations, and potential implications.
• Maintain documentation covering data sources, model methodology, assumptions, parameter choices, testing procedures, and known limitations.
• Support the development of consistent risk definitions, calculation methods, and reporting standards across relevant analytical processes.
• Collaborate with data engineering and technology teams to improve data availability, analytical infrastructure, and the reliability of recurring risk calculations.
• Evaluate the effect of alternative assumptions and parameter settings on model outputs to understand the sensitivity of conclusions.
• Apply appropriate controls when working with confidential financial information, customer data, and commercially sensitive records.
• Contribute to risk reviews and analytical discussions by presenting evidence-based findings and identifying questions that require additional investigation.
• Recommend improvements to quantitative processes, reporting workflows, and analytical controls based on recurring issues or changes in business requirements.
• Keep informed about relevant developments in quantitative finance, statistical modelling, financial risk measurement, and analytical technology.

Requirements and Qualifications

• Professional experience in quantitative risk analysis, financial risk modelling, quantitative finance, financial analytics, or a closely related discipline.
• Strong quantitative and analytical skills, with a sound understanding of probability, statistics, and mathematical modelling.
• Practical experience using Python, R, MATLAB, or comparable tools for quantitative analysis and data processing.
• Strong SQL skills or the ability to work effectively with structured data extracted from relational databases.
• Understanding of financial markets, financial instruments, risk measurement, or relevant financial business processes.
• Experience conducting sensitivity analysis, scenario analysis, statistical testing, or other quantitative investigations.
• Ability to evaluate model assumptions, identify limitations, and assess whether analytical results are appropriate for the question being investigated.
• Familiarity with data cleaning, exploratory analysis, outlier investigation, and validation of model inputs.
• Understanding of relevant risk concepts, potentially including market risk, credit risk, liquidity risk, counterparty exposure, or operational risk.
• Ability to communicate technical findings to stakeholders who may not have advanced quantitative backgrounds.
• Strong attention to detail and a structured approach to documenting analytical methods and results.
• Familiarity with version control, reproducible analytical workflows, and automated testing is advantageous.
• Experience with financial time-series data, portfolio analysis, or risk reporting frameworks is beneficial.
• Ability to manage analytical assignments independently while collaborating effectively with distributed teams.
• A degree in mathematics, statistics, economics, financial engineering, quantitative finance, physics, or a related field is advantageous; equivalent professional experience is also valued.
• Professional proficiency in English is required; knowledge of Estonian is an advantage.

Benefits

• Fully remote working arrangement within Estonia.
• Full-time, permanent employment in a quantitative risk and financial analytics function.
• Opportunities to work with statistical modelling, financial data, risk measurement, and scenario analysis.
• Collaboration with risk, finance, data, and technology professionals.
• Opportunities to contribute to model validation, analytical automation, and improvements in risk reporting.
• Professional development through quantitative projects, technical reviews, and exposure to different risk methodologies.
• An environment that values analytical accuracy, transparent assumptions, responsible data handling, and continuous improvement.
• Opportunities to develop deeper expertise in quantitative risk analysis and data-driven financial decision support.

Application Instructions

Applicants should submit an up-to-date CV outlining their quantitative analysis experience, financial risk knowledge, and technical skills. Highlight experience with Python or R, SQL, statistical modelling, scenario analysis, risk reporting, and financial datasets.

Candidates may include a portfolio, research summary, or project description demonstrating their approach to quantitative modelling, sensitivity analysis, or risk measurement. Supporting examples should exclude confidential employer information, proprietary models, personal data, and restricted financial datasets.

Applications will be assessed on quantitative reasoning, programming proficiency, financial risk understanding, model evaluation, and the ability to communicate analytical findings. Please apply through the official application channel associated with the vacancy and provide only information relevant to your qualifications and experience.

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