Responsibilities:
• Conducting research on on investment sectors and build insights through regression, ML models, etc.
• Develop, Build and Maintain systematic, automated machine learning models to project
localized economic trends into actionable products.
• Collaborate with internal stakeholders and portfolio companies to make sure models meet
business needs, are actively monitored, and are scalable
• Ability to interpret complex economic problems and break down research projects into
structured machine learning research projects.
• See through the end-to-end deployment of machine learning solutions, incorporating some
back-end data engineering workflows via cloud-based solutions (prototype to production
deployment)
• Drive continuous improvement and best practices for the team’s data quality and
ultimately model performance
Qualifications:
• Strong academic background in a relevant field (Computer Science, Engineering)
• 4+ Years of professional experience in an environment prioritizing accuracy and quality of
work
• Highly proficient of a scientific computing language (Matlab, Python, Perl, R, etc.) and
expert with common software/database development flows and tools (Linux, git,
AWS/Azure, SQL (Snowflake), NoSQL (MongoDB), etc.)
• Strong expertise in AI/ML platform engineering, modern data platforms and data structures
interfacing within cloud-based environments
• Experience within AI/ML pipelines, MLOps and production ML/Deep Learning models
(exposure across training, evaluating and deploying solutions)
• Demonstrated workflow and time management skills capable of advancing multiple
projects with varying timelines
• Open to critical thinkers inside and outside of the financial industry, searching for
passionate individuals interested in disrupting a legacy sector
• Ability to work decisively under time pressure from time to time
