About the role
The Senior Quantitative Researcher will have the opportunity to try to „crack“ the financial markets, learn a lot, and have some fun while at it. They will be working with top-quality financial and alternative data, cutting-edge infrastructure, and vast computational resources to find a systematic and sustainable advantage in the markets. The role will involve partnering and growing together with experienced investment professionals, data scientists, and software developers in a team-based environment in the office. The work will be both intellectually challenging and satisfying and the researcher will be rewarded proportionately to the out-of-sample performance of their models. PharVision is committed to providing flexible career development and long-term growth opportunities.
Beyond that, the PharVision team values self-awareness, intellectual curiosity, and a team-player mentality. You will be working side-by-side and learning from experienced investment professionals and quantitative researchers.
Responsibilities
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Research, design, develop and deploy advanced predictive machine learning models (hands-on)
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Develop and implement systematic trading strategies, based on the model predictions
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Read financial literature and academic papers in search of market inefficiencies and inspiration
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Form hypotheses in relation to market patterns and dependencies and test them rigorously
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Learn about financial markets and instruments and find ways to predict their future performanc
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Think creatively, innovate and solve complex problems
Technical Requirements
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At least a graduate degree in a technical field
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Eagerness to learn about financial markets and ways to predict performance of businesses and their stock prices
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5+ years of experience analyzing large amounts of data using Python or R
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Extensive experience training and implementing models with Scikit-learn, Pytorch and/or Tensorflow
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Understanding of linear algebra, time series analysis, data mining, numerical methods, and statistical tools, including PCA and regression
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A track record of demonstrated dedication and perseverance in solving complex problems
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Excellent English, both spoken and written
Soft skills requirements
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Excellent communication skills, both written and oral
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Self-awareness, intellectual curiosity, and a team-player mentality
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Self-starter, enthusiastic and positive thinker
Nice to Have
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Degree(s) in a technical or quantitative discipline, like statistics, mathematics, physics, electrical engineering, or computer science
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Exposure to packages such as pandas, NumPy, statsmodels, sklearn, scipy, matplotlib, and TensorFlow. C++ experience is an advantage
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Exposure to the Agile approach and methodology
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Experience or at least interest in machine learning techniques, time series analysis, and econometrics
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Experience in Deep Learning: DNN, CNN, RNN/LSTM, GAN, or other autoencoders
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KX / KDB+ / q experience
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Basic understanding of equity markets
Company Culture
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Meritocratic, Ego-free, highly driven team environment
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Perpetual personal and academic development – top-notch Wall St and technology research library of materials (courses, books, research papers, webcasts, etc.)
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Challenging problems and innovative problems to solve every day
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Opportunity to innovate and explore research projects of personal interest, while making a meaningful impact on the business
Benefits & Work Conditions
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Work hours: usually 8 am – 6 pm Sofia time, 100% in the office. Off days on some US (New York Stock Exchange) holidays, (not Bulgarian holidays)
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28 days of paid time off (includes 6 sick days)
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Multiple parking and garage spots in the office building
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Unlimited high-quality espresso and coffee in the office
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Lunch is provided in the office on Mondays and Fridays
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Healthy snacks and beverages in the office
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Free fitness/gym subscription
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Subsidy towards additional health insurance
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Team building events
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Modern office with a pleasant environment, high-tech equipment, and a great location – 180-degree city and mountain views from the top floor
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Office kitchen (microwave, fridge, espresso machine, etc.) and 2 bathrooms
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Referral program for bringing in new talent
We are proud to be an equal-opportunity workplace. We do not discriminate based on race, religion, color, national origin, sex, sexual orientation, gender identity/expression, age, status as a protected veteran, status as an individual with a disability, or any other applicable legally protected characteristics.