CIO Business Intelligence

SEPTEMBER 2, 2022

But financial services companies need skilled IT professionals to help manage the integration of new and emerging technology, while modernizing legacy finance tech. As demand for tech skills grows in the finance industry, certain IT jobs are becoming more sought-after than others. Back-end software engineer.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

But financial services companies need skilled IT professionals to help manage the integration of new and emerging technology, while modernizing legacy finance tech. As demand for tech skills grows in the finance industry, certain IT jobs are becoming more sought-after than others. Back-end software engineer.

Finance 98

Finance IT Software Reporting 98

Cloudera

APRIL 19, 2023

Data has become an essential driver for new monetization initiatives in the financial services industry. For example, a retail bank can use customer transaction data to develop personalized financial products, such as credit cards and investment portfolios, tailored to individual needs.

Data-driven 69

Data-driven Data Architecture Measurement Risk 69

Sisense

SEPTEMBER 3, 2020

Besides strong technical skills (for instance, use of Hadoop, programming in R and Python , math, statistics), data scientists should also be able to tackle open-ended questions and undirected research in ways that bring measurable business benefits to their organization. See an example: Explore Dashboard.

Statistics 97

Statistics Metrics Visualization Finance 97

Cloudera

MARCH 18, 2021

The Fundamental Review of the Trading Book (FRTB), introduced by the Basel Committee on Banking Supervision (BCBS), will transform how banks measure risk. In order to help make banks more resilient to drastic market changes, it will impose capital requirements that are more closely aligned with the market’s actual risk factors.

Risk 55

Risk Machine Learning Risk Management Measurement 55

O'Reilly on Data

OCTOBER 18, 2022

As AI technologies are adopted more broadly in security and other high-risk applications, we’ll all need to know more about AI audit and risk management. applies external authoritative standards from laws, regulations, and AI risk management frameworks. Bias is about more than data and models.

Risk Management 291

Risk Management Risk Testing Measurement 291

Domino Data Lab

FEBRUARY 4, 2019

Eric’s article describes an approach to process for data science teams in a stark contrast to the risk management practices of Agile process, such as timeboxing. As the article explains, data science is set apart from other business functions by two fundamental aspects: Relatively low costs for exploration.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66