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PharVision Capital

Senior Quantitative Researcher / Data Scientist / Machine Learning

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    Tech Stack / Изисквания

    About PharVision Capital

    PharVision Capital is a quantitative hedge fund, founded in 2020 in Chicago to capture opportunities in the US-listed equity markets, using big data and machine learning. PharVision is looking to deliver superior uncorrelated returns to its investors through a machine-plus-man approach. The team is utilizing proprietary quality data sources, sound economic reasoning, machine learning signal generation, vast computational resources, and airtight portfolio risk management to drive performance. The culture is centered around meritocracy, collaboration, innovation, creativity, overcommunication, urgency, and relentless ambition to grow our intellectual competitive advantage.

    Our team of quantitative researchers, mathematicians, and machine learning experts strives to develop breakthrough solutions to some of the most challenging problems in finance and economics. To achieve that, we rely on a robust data pipeline and software infrastructure in order to continue operating smoothly.

    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

    • Research, design, develop and deploy advanced predictive machine learning models (hands-on)
    • Develop and implement systematic trading strategies, based on the model predictions
    • Read financial literature and academic papers in search of market inefficiencies and inspiration
    • Form hypotheses in relation to market patterns and dependencies and test them rigorously
    • Learn about financial markets and instruments and find ways to predict their future performance
    • Think creatively, innovate and solve complex problems

    Technical Requirements

    • At least a graduate degree in a technical field
    • Eagerness to learn about financial markets and ways to predict performance of businesses and their stock prices
    • 5+ years of experience analyzing large amounts of data using Python or R
    • Extensive experience training and implementing models with Scikit-learn, Pytorch and/or Tensorflow
    • Understanding of linear algebra, time series analysis, data mining, numerical methods, and statistical tools, including PCA and regression
    • A track record of demonstrated dedication and perseverance in solving complex problems
    • Excellent English, both spoken and written

    Soft skills requirements

    • Excellent communication skills, both written and oral
    • Self-awareness, intellectual curiosity, and a team-player mentality
    • Self-starter, enthusiastic and positive thinker

    Nice to Have

    • Degree(s) in a technical or quantitative discipline, like statistics, mathematics, physics, electrical engineering, or computer science
    • Exposure to packages such as pandas, NumPy, statsmodels, sklearn, scipy, matplotlib, and TensorFlow. C++ experience is an advantage
    • Exposure to the Agile approach and methodology
    • Experience or at least interest in machine learning techniques, time series analysis, and econometrics
    • Experience in Deep Learning: DNN, CNN, RNN/LSTM, GAN, or other autoencoders
    • KX / KDB+ / q experience
    • Basic understanding of equity markets

    Company Culture

    • Meritocratic, Ego-free, highly driven team environment
    • Perpetual personal and academic development – top-notch Wall St and technology research library of materials (courses, books, research papers, webcasts, etc.)
    • Challenging problems and innovative problems to solve every day
    • Opportunity to innovate and explore research projects of personal interest, while making a meaningful impact on the business


    Benefits & Work Conditions

    • Work hours: flexible, 100% in the office. Off days on some US (New York Stock Exchange) holidays, (not Bulgarian holidays)
    • 28 days of paid time off (includes 6 sick days)
    • Continued education and learning – unlimited free SoftUni courses 
    • Multiple parking and garage spots in the office building
    • Unlimited high-quality espresso and coffee in the office
    • Lunch is provided in the office on Mondays and Fridays
    • Healthy snacks and beverages in the office
    • Free fitness/gym subscription
    • Special PharVision dIscounts at various retailers
    • Subsidy towards additional health insurance
    • Team building events
    • Modern office with a pleasant environment, high-tech equipment, and a great location – 180-degree city and mountain views from the top floor
    • Office kitchen (microwave, fridge, espresso machine, etc.) and 2 bathrooms
    • 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.