Exness
Fintech
QuantitativeResearcher
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Quantitative Researcher at Exness. Skills: Quantitative research, Financial markets, Econometrics, Machine learning. Analyze financial market data. Analyze industry trends”
Industry & Context.
Analytical skills; Problem-solving skills
What They're Looking For.
Must Have
Bachelor's or Master's degree in Mathematics, Statistics, Econometrics, Data Science, Computer Science, Finance, or related quantitative field, 1+ years of experience as Quant, Data Analyst or Data Scientist, Understanding of financial markets, Proficiency in SQL, Python/R, Understanding of statistics and econometrics, Experience in building mathematical, statistical or time-series models
Nice to Have
PhD preferred, Knowledge of asset pricing, financial econometrics, derivatives, and market microstructure is a plus, Experience with market microstructure data is beneficial
What You'll Do.
Analyze financial market data
Analyze industry trends
Identify opportunities for new projects
Identify opportunities for product enhancements
Conduct competitor analysis
Benchmark product offerings
Support strategic positioning
Perform deep analysis of complex financial datasets
Analyze market microstructure data
Design econometric models
Build econometric models
Validate econometric models
Design machine learning models
Build machine learning models
Validate machine learning models
Design time-series models
Build time-series models
Validate time-series models
Apply statistical techniques
Apply econometric techniques
Improve decision-making
Ensure model robustness
Ensure model reliability
Ensure model alignment with business objectives
Formulate research hypotheses
Design analytical approaches
Translate quantitative findings into recommendations
Provide analytical input for new products
Provide analytical input for new initiatives
Provide analytical input for market expansion
Collaborate with stakeholders
Work with large datasets
Work with complex datasets
Ensure data integrity
Ensure reproducibility
Ensure analytical accuracy
Document methodologies
Document model limitations
Support model productionization
Prepare analytical reports
Prepare presentations
Communicate quantitative concepts
Support stakeholders in interpreting results
Support stakeholders in understanding risks
Support stakeholders in understanding assumptions
How You'll Work.
Team & Collaboration
Cross-functional stakeholders; Developers; Analysts; QA; Project owners; International team environment
Communication Scope
Written communication; Communicate complex concepts; Communicate findings
Full Job Description
At Exness, we are not just a leading trading broker—we’ve reimagined what it takes to be a leader. With 40M+ trades a day and 2,000+ people across 13 countries, we combine scale, care, and real tech to make trading better for 1M+ clients worldwide. Recognised globally as a Best Place to Work, we’re a people-first company where long-term wins always matter more. As part of our team, you will shape the future of fintech with real technology, care, and purpose. Why this role matters A Quantitative Researcher is responsible for conducting data-driven research and advanced quantitative analysis to support the development and optimization of financial products and strategic initiatives. The role focuses on analyzing financial market data, building mathematical/statistical models/logics, econometric and machine learning models, validating hypotheses, and providing analytical insights to inform product and business decisions, particularly in support of expansion into new markets. The role is based in our office in Limassol, Cyprus. In case of relocation, we offer full relocation support for you and your family to make your move smooth and worry-free. What you'll actually do Analyze financial market data and industry trends to identify opportunities for new projects and product enhancements. Conduct competitor analysis, including trading conditions and related parameters, to benchmark product offerings and support strategic positioning. Perform deep analysis of complex financial datasets, including market microstructure data where applicable. Design, build, and validate econometric and machine learning models, including robust time-series models using modern approaches. Apply statistical and econometric techniques to extract insights and improve forecasting and decision-making capabilities. Ensure model robustness, reliability, and alignment with business objectives. Formulate research hypotheses based on financial and market data. Design experiments and analytical approache
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