About the Role

The Senior Python Developer will be expected to design, build and iterate on components of the machine learning software and the quantitative research infrastructure. The Senior Developer will be a key pillar of our core business and will be an inseparable member of the team, fully integrated and in sync with the MLOps and research process. Critical thinking will be required on a daily basis to evaluate and prioritize projects, as well as solve complex problems. Planning, time management, and the ability to clearly communicate both the benefits and the limitations of different solutions and approaches is key. The ideal candidate is someone with extensive Python, AWS, Docker, MLOps experience, combined with a creative mindset and data awareness. 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, data engineers and quantitative ML researchers.

PharVision is committed to providing flexible career development and growth opportunities.

Responsibilities

• Design, develop, test, and maintain software solutions (hands-on)
• Build CI/CD pipelines
• Think critically and improve the existing internal software
• Think creatively, innovate and solve complex problems
• Lead and mentor the rest of the team and help implement best practices in coding

Technical Skillset Requirements

• Ideally, 8+ years of experience programming in Python
• Proficiency in cloud computing (preferably AWS)
• Experience working with docker containers
• Experience working with large data sets
• Experience working with task scheduling and DAGs
• Exposure to unit and integration testing frameworks
• Proficiency in Git

Soft skills requirements

• Great 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
• Understanding of time series analysis, data mining, numerical methods, and statistical tools, including PCA and regression
• 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