Hybrid Data Scientist/ML Engineer Data Scientist/ML Engineer

AudaCity Capital is a progressive and flourishing prop trading firm, and trading education provider. We are based in London, and at the moment have a team of highly trained properly trading professionals, managing the company’s extensive funds on our City of London based trading floor.We believe that the only way to be a winner in our industry is to invest heavily in talented people who want to grow with us. We are seeking like-minded professionals to develop their skills and enable them to join our team.We trade on all major asset classes on multiple exchanges with our own capital and do not handle any client funds or have customers. By becoming a member of the team, you become part of our success. We are market leaders because we have always had an internal vision to promote a strong entrepreneurial working culture.Our mission statement is to mix a strong base of intellectual capital with state-of-the-art technology, to build for the future. Our trading has a unique combination of skills, talent, and industry-leading software, which has been produced in-house by the company development department.Strict, Prudent Risk ManagementYou can have guts, but not glory, if you don’t back your trading moves with proper management practices. That’s why we treat risk management with the utmost seriousness …The RoleYou Will Be Responsible For

• Developing scripts to process structured and unstructured data.
• Recommending, developing and implementing ways to improve data reliability, efficiency and quality.
• Supporting translation of data business needs into technical system requirements.
• Working with stakeholders to understand needs in order with respect to data structure, availability, scalability and accessibility.
• Defining, developing and maintaining reports to support decision making.
• Processing & Interpreting data to get actionable insights.
• Working closely with business users to understand their data analysis needs/requirements.
• Developing high-quality code to build and deploy machine learning models.
• Identifying trends, doing follow-up analysis, preparing visualizations.