Senior Quantitative Researcher - HFT - Trader @ Amazon

Job Description

quantitative researcher / hybrid / full time About us: Universis Capital Partner is an alternative investment fund with a management capacity of up to USD 500 million, carried out in phases of USD 100 million. We manage financial assets with the best resources in analytics and management, adapted to both traditional and digital assets, based on cryptocurrency infrastructure and blockchain technologies. We provide liquidity in markets and assets, trading, market maker, project finance, venture capital, early stage tokens and liquid tokens, with a total of 12 management lines divided into 3 groups. We build strategic alliances with major partners (Funds, Labs, Venture, Market Maker) globally, which strengthen joint institutional management and streamline our contribution of liquidity in trading and top-tier projects. We work with sophisticated traders, token issuers, funds, professional investors, regulated trusts and major exchanges worldwide. Our growing team is formed by the. best senior professionals in each specialty, with more than 9 years of experience in commercial management, algorithmic development, financing and investment in projects. We generate close relationships with the promoters of the projects in which we participate, providing investment and liquidity in key stages; Seed and Series A. Who are we looking for: Senior Quantitative Researcher - HFT - Trader We are looking for a senior quantitative alpha researcher with deep knowledge in signal research and special interest in high frequency trading, cryptocurrencies, market making and options. The objective is to work directly with our team of traders and engineers, for the development of management systems. Localization, monitoring and execution will be part of your duties. The ideal candidate would be passionate about algorithmic and crypto trading, specialist in alpha generation. With knowledge in algorithmic trading based on Data Mining, Big data, Quants, Machine Learning, with predictive and risk management capabilities to implement high frequency and low latency systems, HFT, Market Making, arbitrage systems. Responsibilities: Design, develop and help implement high-frequency commercial algorithms. In-depth knowledge of Alpha Signal analysis and signal generation. Analysis and design of improvements in the execution of current signals. Code development, advanced simulation systems and tick-by-tick backtesting. Analyze performance management by improving risk, quantification. Interact directly with the business or provide support to the commercial, development and operational teams, supervising to implement changes, technological improvements and solve incidents or problems. Monitoring and follow-up of execution. Participate in product quality control. Collaborate with other teams, including; strategy reviews, code and common programming advice. Requirements: Academic or postgraduate quantitative training; Applied Mathematics, Statistics, Finance, Financial Engineering, Computer Science. Basic experience in C++ or Python. An analytical and problem-solving mindset. Ability to work independently, but in a collaborative team environment. Deep curiosity about financial trading and the digital blockchain ecosystem. Entrepreneurial mindset, persistent and disciplined with a high degree of motivation and involvement. High level of English, fluent oral and written communication. Experience: More than 3 years of experience as an Alpha analyst, signal generation, statistical modeling, in high frequency trading companies, is essential: banking, funds, management companies. Experience in Machine Learning, Data Mining, Big data, Neural Networks, artificial intelligence, algorithms, numerical analysis or stochastic calculus is essential. Experience in collaborating in the development of financial algorithms, with predictive analytics and risk control, is desirable. Experience in financial product analytics; Algorithmic, High Frequency Trading, Derivatives Trading, Options trading. Evaluation criteria: Provide figures, documents, analyses or studies. Trading history developed with your analytics. Examples of returns, with maximum drawdown. Maximum volume of capital managed (only in the case of having managed with your analytics). Performance and risk management evaluation of your trading skills or strategies. Have worked in companies in the financial sector, in high-frequency systems and market creation. Main Sectors of interest: All types of liquid assets, in particular: Cryto, Forex, Stock Market, Commodities, Bonds, Indexes, Options. What we offer: Type of work: Permanent + Freelance + Remote. Valuation and remuneration according to performance. Fixed gross salary linked to objectives, plus 2 extra annual bonuses. Extra incentives based on performance. Extra management and participation income. Total autonomy in managing your time thanks to flexible working hours and the opportunity to work remotely. Possibility of internal promotion to higher positions. Policy against discrimination: At Universis Capital we promote equal employment opportunities. We pride ourselves on being a mutli-cultural team. We do not discriminate against anyone on the basis of race, color, gender, age, origin, religion, sexual orientation, gender identity or expression, marital status, citizenship, disability. We treat our colleagues and candidates fairly. We follow all related laws and in our employment decisions (such as recruiting, hiring, training, salary and promotion

Employement Category:

Employement Type: Full time
Industry: Others
Role Category: General / Other Software
Functional Area: Not Applicable
Role/Responsibilies: Senior Quantitative Researcher - HFT - Trader

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Keyskills:   quantitative research high frequency trading market making options data mining big data machine learning risk management C Python statistics finance financial engineering computer science neural networks artificial intelligence numerical analysis stochastic calculus derivatives trading cryptocurrencies algorithmic trading quants options trading