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Quantitative Trading Analyst - poste à distance

Qompyl

Depuis partoutÀ distance
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Le lien mène à l'annonce d'origine. Donator ne reçoit aucune candidature.

Publiée : (il y a 10 jours)Active : jusqu'au 25 novembre 2026

Quantitative Trading Analyst - Data et analytics, à distance

L'entreprise Qompyl recrute : Quantitative Trading Analyst. Le poste relève de la catégorie Data et analytics et se fait entièrement à distance. Aucune restriction n'est posée sur le lieu de résidence du candidat, vous pouvez donc postuler de partout.

L'entreprise n'a publié aucun chiffre, cela se règle en entretien. L'annonce ne pose aucune condition d'horaires.

Cette offre a passé un contrôle automatique : les annonces qui exigent un permis de travail étranger, un parrainage de visa, une nationalité précise ou une résidence dans un pays nommé n'entrent pas dans la liste.

En bref

Entreprise
Qompyl
Catégorie
Data et analytics
Qui peut postuler
De n'importe quel pays du monde
Mode de travail
Entièrement à distance
Type de contrat
Temps partiel
Publiée
26 septembre 2026 (il y a 10 jours)
Validité
jusqu'au 25 novembre 2026
Origine
Himalayas

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La description de l'entreprise

About Qompyl Qompyl is an early-stage fintech startup building a no-code platform that enables users to create, backtest, analyze, and monitor trading strategies. Our mission is to make sophisticated quantitative trading tools more intuitive, visual, and accessible. We are developing a platform where accuracy, data integrity, and sound financial logic are essential to delivering a reliable and trustworthy user experience. About the Role We are looking for a Quantitative Trading Analyst to help research, build, test, and improve trading strategies, indicators, and quantitative trading functionality within Qompyl . This is a hands-on and cross-functional role combining quantitative research, systematic trading, indicator and signal development, strategy analysis, product validation, and product collaboration . We are specifically looking for someone with a mathematically and statistically driven approach to trading . The ideal candidate can take a market hypothesis or trading idea, translate it into measurable rules or signals, test it rigorously using historical data, and critically evaluate whether the resulting performance is statistically and financially meaningful. You will work directly with Qompyl 's indicators and strategy-building tools: researching and developing indicators and signals, validating their mathematical and financial logic, building and backtesting systematic strategies, analyzing performance and risk, and identifying opportunities to improve the platform. You will also work closely with our product and trading teams to translate quantitative trading concepts into intuitive tools that traders can use without needing to code. This is not a traditional software QA role or a purely discretionary trading role . We are looking for someone who combines financial-market knowledge with quantitative thinking, enjoys experimenting with data and models, and can contribute to an evolving trading product. Core Responsibilities Quantitative Research & Signal Development

* Research quantitative trading ideas, signals, indicators, and market relationships.

* Translate market hypotheses into measurable, testable quantitative rules .

* Apply statistical and mathematical methods to evaluate signal quality and robustness.

* Analyze relationships across prices, returns, volatility, volume, momentum, market regimes, and other relevant market variables.

* Identify noise, overfitting, unstable relationships, and potential biases.

* Evaluate whether observed patterns are economically and statistically meaningful.

* Document research methodology, assumptions, findings, and limitations.

Indicator Creation & Validation

* Research and create new trading indicators and quantitative signals for the Qompyl platform.

* Define indicator logic, formulas, parameters, signals, and expected behavior.

* Validate calculations and outputs for mathematical and financial correctness.

* Test indicators across different assets, time periods, market regimes, and parameter configurations.

* Identify edge cases, unstable behavior, misleading signals, or unintended relationships.

* Collaborate with trading and product teams to improve Qompyl 's indicator library.

* Translate quantitative concepts into intuitive functionality within the Strategy Builder.

Systematic Strategy Development & Backtesting

* Build and test systematic trading strategies using Qompyl and analytical tools such as Python .

* Combine signals, indicators, market conditions, and risk rules to research different strategy hypotheses.

* Analyze entries, exits, position sizing, portfolio allocation, returns, P&L, drawdowns, volatility, Sharpe ratio, and other relevant performance and risk metrics.

* Design rigorous backtests and critically evaluate their results.

* Account for potential issues such as overfitting, look-ahead bias, survivorship bias, transaction costs, slippage, and parameter sensitivity .

* Perform out-of-sample, robustness, and scenario testing when appropriate.

* Challenge results that appear statistically or financially unrealistic.

* Compare strategy behavior across different assets and market regimes.

Product Collaboration

* Work closely with Qompyl 's product, engineering, data, and trading contributors.

* Bring a quantitative trading perspective to new indicators, strategy-building functionality, analytics, and product features.

* Help determine whether proposed quantitative features are mathematically sound and useful to traders.

* Translate quantitative research into clear product requirements and user-friendly functionality.

* Participate in brainstorming and exploration of new trading and research tools.

* Help bridge the gap between quantitative research and an intuitive no-code trading experience .

Trader & Community Feedback

* Engage with traders and beta users to understand how they build and evaluate strategies.

* Gather feedback on indicators, strategy analytics, and quantitative functionality.

* Identify recurring needs that could become new signals, indicators, analytics, educational resources, or product improvements.

* Explain quantitative trading concepts clearly to users with different levels of technical expertise.

Required Skills & Experience

* Strong quantitative foundation in mathematics, statistics, probability, econometrics, engineering, computer science, physics, quantitative finance, or a related discipline .

* Hands-on experience with quantitative research, systematic trading, algorithmic trading, or quantitative strategy development .

* Strong understanding of statistical analysis and its application to financial markets.

* Experience researching and testing trading signals or systematic strategies.

* Strong understanding of backtesting methodology and common sources of bias.

* Ability to analyze strategy performance using risk and return metrics.

* Proficiency with Python for quantitative analysis, research, or backtesting.

* Strong practical understanding of financial markets and trading mechanics.

* Understanding of entries, exits, order logic, position sizing, risk, P&L, returns, volatility, and drawdowns.

* Ability to critically evaluate whether quantitative results are statistically and financially reasonable.

* Strong analytical mindset, attention to detail, and healthy skepticism.

* Ability to communicate quantitative concepts clearly to both technical and non-technical collaborators.

* Comfortable working independently in a remote, asynchronous, early-stage startup environment.

Preferred Qualifications

* Degree or advanced coursework in mathematics, statistics, quantitative finance, econometrics, engineering, physics, computer science, or another highly quantitative discipline.

* Experience with NumPy, pandas, SciPy, statsmodels, scikit-learn , or similar quantitative/data-science libraries.

* Experience with time-series analysis, statistical modeling, optimization, factor research, or machine learning applied to financial markets.

* Experience creating or modifying trading indicators.

* Familiarity with TradingView, Pine Script, or other strategy-building/backtesting platforms.

* Experience working with stocks, ETFs, futures, forex, cryptocurrencies, or derivatives.

* Experience with SQL and financial datasets.

* Experience contributing to a fintech, trading, analytics, or investment product.

* Product-oriented or entrepreneurial mindset.

* Experience communicating quantitative research or trading concepts to broader audiences.

Working at Qompyl

You will work closely with Qompyl 's product, engineering, data, and trading contributors to ensure the platform is quantitatively sound, financially accurate, technically reliable, and genuinely useful to traders . This role requires curiosity, precision, ownership, and healthy skepticism…

Le texte est conservé dans la langue d'origine de l'entreprise, car c'est dans cette langue que vous postulerez.

Cette offre a été publiée sur Himalayas. Annonce d'origine (Himalayas)

Questions fréquentes sur cette offre

Puis-je postuler au poste de Quantitative Trading Analyst depuis là où je vis ?

Oui. Pour cette offre, Qompyl accepte des candidats de n'importe quel pays du monde, vous n'avez donc besoin d'aucun permis de travail pour un autre pays. L'annonce a passé un contrôle automatique : si l'entreprise avait exigé un permis de travail, un parrainage de visa ou une résidence dans un pays précis, elle ne figurerait pas sur ce tableau.

Quelle rémunération est indiquée ?

Pour cette offre, Qompyl n'a publié aucune rémunération. La plupart des annonces à distance ne donnent aucun chiffre, cela se règle en entretien.

Comment postuler ?

Vous postulez directement auprès de l'entreprise, via l'annonce d'origine publiée sur Himalayas. Donator ne reçoit aucune candidature, ne prend aucune commission et ne conserve aucun CV.

De quel type d'offre s'agit-il ?

Un poste entièrement à distance dans la catégorie Data et analytics. Les annonces hybrides et tout ce qui impose une présence au bureau ne sont pas publiés sur ce tableau.

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