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PharVision Capital

Data Engineer (Python/Pandas/Airflow/AWS)

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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

    As a Data Engineer at a quantitative hedge fund, you will play a critical role in designing, building and maintaining the firm’s data infrastructure, which is a foundational component of our investment strategies. Your primary responsibilities will include identifying useful datasets, which could give us an informational advantage over other investors, and then collecting and processing those datasets. You will also develop data quality controls to ensure data accuracy and integrity, and you will work with software engineers to integrate the data infrastructure with other systems and applications.You will work closely with the investment team, data scientists, and software engineers to ensure that the data pipeline is optimized for performance, reliability, and scalability.

    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 highly experienced investment professionals, softare engineers and quantitative researchers.

    If you are passionate about leveraging technology to drive investment insights and thrive in a fast-paced, collaborative environment, we encourage you to apply for this exciting opportunity.

     

    Responsibilities

    • Design, build, and maintain the firm’s data infrastructure using Python, Pandas, Apache Airflow and other relevant tools
    • Implement ETL processes to collect, clean, and transform data from a variety of sources
    • Collaborate with the researchers to identify and evaluate datasets potentially useful to the investment process
    • Optimize data processing pipelines for performance and scalability using AWS and other cloud technologies
    • Develop data quality controls to ensure data accuracy and integrity
    • Work with software engineers to integrate the data infrastructure with other systems and applications
    • Stay up-to-date with the latest developments in data engineering and contribute to the development of best practices within the firm

     

    Technical Requirements

    • At least a graduate degree in a technical field
    • Eagerness to learn about financial markets and ways to gain an informational advantage over the competition
    • 5+ years of experience in data engineering or a related field
    • Strong programming skills in Python and experience working with Pandas
    • Experience with AWS or other cloud technologies
    • Familiarity with data modeling and database design concepts
    • Experience with ETL processes and tools
    • Excellent problem-solving skills and attention to detail
    • Strong communication skills and ability to work collaboratively in a team environment


    Nice to Have

    • KX / KDB+ / q experience
    • 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
    • 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
    • Office kitchen (microwave, fridge, espresso machine, etc.) and 2 bathrooms
    • 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
    • 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.