Protize partnered with Midori Investments to build and scale a data science function for investment research, portfolio strategy, and IT risk controls using Node, Python, AI/ML, and Azure.
Client
Midori Investments
Date
April 2020
Duration
Apr 2020 – Jul 2021
Protize established and led a dedicated data science function for Midori Investments to accelerate research quality, portfolio strategy, and decision velocity. The engagement combined analytics modernization with strong IT risk controls to support secure, data-driven investment operations.
Midori required a robust analytics-led framework for evaluating multi-asset opportunities across stocks, securities, and derivatives. At the same time, the firm needed stronger security and governance controls for proprietary research data, models, and development workflows.
The organization needed structured and repeatable processes for investment research, portfolio review, and allocation strategy. Existing risk readiness and security posture also required modernization to meet finance-grade expectations for confidentiality, control, and operational assurance.
Protize designed a scalable operating model for research and portfolio analytics, including model-driven evaluation and quarterly review workflows. We also strengthened infrastructure and process controls through encrypted storage, secure developer access via VPN, and self-hosted source control governance on Azure-backed environments.
Node.js
Python
AI/ML
Azure
Data Science
Investment Models
Portfolio Review
Asset Allocation
Security
Risk Assessment
Encrypted Storage
Self-Hosted Git
VPN
Protize built and led the data science capability end-to-end, aligning research execution, model governance, and infrastructure security standards for sustained investment operations.
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