{"id":76161,"date":"2024-03-04T12:45:27","date_gmt":"2024-03-04T12:45:27","guid":{"rendered":"https:\/\/www.taylorroot.com\/?p=76161"},"modified":"2026-04-14T09:18:02","modified_gmt":"2026-04-14T09:18:02","slug":"what-do-the-data-engineering-and-data-science-workforces-within-insurance-look-like","status":"publish","type":"post","link":"https:\/\/srgroup.highrise.digital\/zh-hans\/market-insight\/industry-leaders\/what-do-the-data-engineering-and-data-science-workforces-within-insurance-look-like\/","title":{"rendered":"What do the Data Engineering and Data Science workforces within insurance look like?"},"content":{"rendered":"\n
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In recent years, the insurance industry has undergone a significant transformation, leveraging advancements in technology and data to revolutionise operations and enhance competitiveness. Data plays a crucial role in decision-making processes across various functions, from underwriting and claims processing to customer engagement and risk management.<\/p>\n\n\n\n

We have taken a  snapshot of key data points on demographics, career trends, and educational backgrounds and this reveals intriguing themes and opportunities.<\/p>\n\n\n\n

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Download above stats<\/a><\/div>\n<\/div>\n\n\n\n

Data Science and Data Engineering trends:<\/u><\/strong><\/h2>\n\n\n\n

Gender gap<\/h2>\n\n\n\n

The data reveals distinct patterns in the demographics and qualifications of professionals in Data Science and Data Engineering roles within the insurance sector. The key and most notable factor, which is being discussed by the industry with more fever than ever before, is the gender gap.<\/p>\n\n\n\n

Whilst improvements have been made over the past few years, the industry is still lagging behind competitive industries such as banking and financial services.<\/p>\n\n\n\n

Within the UK insurance market, women represent 24% of Data Engineers and 27% of Data Scientists, which is somewhat below banking, 34%, and financial services at 31%. Both of these industries have a much larger workforce which highlights further the gap in this figures.<\/p>\n\n\n\n

Typically the gender gap is attributed to: <\/p>\n\n\n\n