Data Analyst - Machine Learning

Creospan is a growing tech collective of makers, shakers, and problem solvers, offering solutions today that will propel businesses into a better tomorrow. “Tomorrow’s ideas, built today!” In addition to being able to work alongside equally brilliant and motivated developers, our consultants appreciate the opportunity to learn and apply new skills and methodologies to different clients and industries. • • • • • • NO C2C/3RD PARTY, LOOKING FOR W2 CANDIDATES ONLY, must be able to work in the US without sponsorship now or in the future • • • Responsibilities • Design, develop, and maintain scalable data-processing pipelines for large volumes of multimedia (audio, video) and sensor data (e.g. IMU), ensuring reliability and reproducibility. • Gather and interpret processing requirements from stakeholders, translating them into practical technical solutions and devising novel approaches where needed. • Perform diverse data-processing operations, from mathematical transformations and filtering to feature extraction, synchronisation, and inference through ML models. • Interface with various internal tooling at Meta such as dataset management systems and training frameworks to prepare raw data for machine learning, including validation, transformation, and quality assurance. • Collaborate with machine learning researchers to integrate research prototypes into production pipelines. • Ensure compliance with data governance, security, and relevant standards. Minimum requirements • Bachelor’s degree in a relevant technical field (e.g. Computer Science, Data Science) with 3+ years of industry experience in machine learning or data engineering; or equivalent combination of education and experience. • Demonstrable programming experience in Python using common ML and data libraries, i.e. numpy, scipy, pandas. • Proficiency in Linux and shell scripting. • Working knowledge of audio, image and video formats. Preferred experience • Experience using PyTorch or other Python machine-learning frameworks. • Experience with relational and graph / NoSQL databases. • Experience using REST APIs for data interactions. • Experience working in a research environment. • Strong mathematical background.