DataRobot

JULY 16, 2021

The first is trust in the performance of your AI/machine learning model. They all serve to answer the question, “How well can my model make predictions based on data?” So, we ask, what recommendations and assessments can you use to verify the origin and quality of the data used? How large is the data set?

Machine Learning 98

Machine Learning Uncertainty Modeling Measurement 98

CIO Business Intelligence

SEPTEMBER 2, 2022

The average salary for a financial software engineer is $116,670 per year, with a reported salary range of $85,000 to $177,000 per year, according to data from Glassdoor. Full-stack software engineers are essentially high-level software engineers who are focused on designing, testing, and implementing software applications.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

The average salary for a financial software engineer is $116,670 per year, with a reported salary range of $85,000 to $177,000 per year, according to data from Glassdoor. Full-stack software engineers are essentially high-level software engineers who are focused on designing, testing, and implementing software applications.

Finance 98

Finance IT Software Reporting 98

FineReport

MARCH 24, 2024

They also develop and support reporting processes, ensure data quality, and collaborate with internal and external stakeholders to understand data content and gather business requirements. Jupyter Notebooks: Simplifies code testing and collaboration for data analysis tasks. JPMorgan Chase & Co.:

Statistics 52

Statistics Data mining Visualization Reporting 52

O'Reilly on Data

JULY 15, 2019

In recent posts, we described requisite foundational technologies needed to sustain machine learning practices within organizations, and specialized tools for model development, model governance, and model operations/testing/monitoring. Note that the emphasis of SR 11-7 is on risk management.).

Machine Learning 38

Machine Learning Management Enterprise Risk Management 38

Cloudera

JUNE 29, 2023

To ensure the stability of the US financial system, the implementation of advanced liquidity risk models and stress testing using (MI/AI) could potentially serve as a protective measure. To improve the way they model and manage risk, institutions must modernize their data management and data governance practices.

Data Architecture 86

Data Architecture Risk Management Risk Management 86

Cloudera

SEPTEMBER 7, 2023

With the emergence of new creative AI algorithms like large language models (LLM) fromOpenAI’s ChatGPT, Google’s Bard, Meta’s LLaMa, and Bloomberg’s BloombergGPT—awareness, interest and adoption of AI use cases across industries is at an all time high. The reality of LLMs and other “narrow” AI technologies is that none of them is turn-key.

Insurance 83

Insurance Risk Data-driven Finance 83

DataRobot Blog

JULY 21, 2022

Document assumptions and risks to develop a risk management strategy. Machine learning models created in silos are rarely implemented. Evaluate the computing resources and development environment that the data science team will need. Models could also be deployed into multiple environments at once.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

DataRobot Blog

DECEMBER 20, 2022

Yet, in the digital transformation era, the pricing and assessment of real estate assets is more difficult than described by brokers’ presentations, valuation reports, and traditional analytical approaches like hedonic models. We’ll then empirically test this assumption based on an example of real estate asset assessment.

Management 59

Management Machine Learning Optimization Modeling 59

datapine

AUGUST 29, 2022

Data Smart’ contains enough practical knowledge to actually start performing analyses by using good old Microsoft Excel. Not only does this digestible guide speak to the reader in a clear, decipherable language, but it is also rich in actionable tips in areas including A/B testing, social network analysis, regression, clustering, and more.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

AWS Big Data

AUGUST 14, 2023

Taken together, the posts in this series lay out some possible operating models for data mesh within an organization. In the same way, organizations seeking to implement successful data mesh strategies must respect the nature and structure (legal, political, commercial, technology) of their organizations in their implementation.

Management 79

Management Risk Measurement Optimization 79

Andrew White

JANUARY 11, 2021

How do you think Technology Business Management plays into this strategy? Where does the Data Architect role fits in the Operational Model ? Assuming a data architect helps model and guide and assist D&A then they play a key role. Value Management or monetization. Product Management. Governance.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52