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Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data,[1][2] and apply knowledge and actionable insights from data across a broad range of application domains.

Data Science

Dig deep into your data and gain insight. Uncover patterns and compute stats you can trust

Data Analysis

Build graphs, KPIs and interfaces which can be used to take business decisions

Data Visualization

AI Data Analysis

Forecasts trends and behaviors using historical data and ML models. Common in finance, marketing, and operations.

Predictive Analytics

Use ML to spot unusual transactions or metrics before they escalate.

Anomaly & Fraud Detection

AI Enterprise Model Tuning

Tracks model performance, bias, drift, and hallucinations in production. Ensures compliance and reliability.

Model Evaluation & Monitoring

A highly regulated industry, today’s finance firms are highly dependent on technology. Their requirements range from highly technical and intensive computational modelling, real-time data analysis, fraud prevention, to front-end needs such as marketing and customer retention, always burdened with the highest security requirements of any private sector. 

Finance

Asset management is a systematic approach to the governance and realization of value from the things that a group or entity is responsible for, over their whole life cycles. It may apply both to tangible assets and to intangible assets.

Asset Management

Investment banking deals primarily with the creation of capital for other companies, governments, and other entities.

Investment Banking

Venture Capital

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Monroe Capital LLC

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Monroe Capital LLC

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