Data Strategy Office,
Joined in 2023
Carrying out data analysis-related projects in collaboration with Dai-ichi Life
The mission of the Data Strategy Office where I work is to contribute to the promotion of digital transformation at Dai-ichi Life and other Dai-ichi Life Group companies through data utilization and to link this to business benefits. In collaboration with Dai-ichi Life's Data Analytics Department, we use tools such as AI and BI to implement a wide range of projects, from management issues to individual business issues.
The theme of the project I'm currently in charge of is "data analysis related to life insurance marketing". Using internal and external data, we are conducting a multifaceted analysis of "Identifying insurance needs across various demographic segments" and using the results in formulating marketing strategies and developing insurance products.
In projects in the data analytics field, we first clarify the analysis requirements after thoroughly understanding the current situation and needs of the business. From there, we break it down into analysis issues, formulate hypotheses, check actual data, extract and process data, analyze data, and evaluate and verify. Finally, we explain it to the business department and have them apply the hypothesis verification results to their business. This is the entire process.
For example, if we are conducting data analysis targeting young people living alone, we must first check data from the Statistics Bureau, Ministry of Internal Affairs and Communications to see how many people in Japan have the attributes of "living alone" and "young people". We analyze basic population data and the latest data from inside and outside the company to clarify the total number and attributes of people that Dai-ichi Life should approach. "Age group" and "family structure" are key indicators when analyzing the expected customer demographic for each insurance product. This is because the needs of insurance products vary greatly depending on whether the person is single or married, whether they have children, etc.
Of course, to make data analysis produce business benefits, it is better to have data science skills, but I think it is also important to have domain knowledge and be able to understand what the business division wants, and to be able to communicate and work closely with them.
Striving to Become a Data Science Expert
I was in charge of data analysis at my previous workplace, but at the same time I was also involved in projects related to data utilization, such as the use of AI scoring models. As I gained experience in data analysis and data utilization, my interest in "data science" grew, and I began to think, "I want to master this field", which is why I considered changing jobs.
The conditions I wanted for my new workplace were, "There should be more opportunities to perform data analysis than in my previous job", and "A workplace with senior employees who are well versed in data science whom I can ask questions of and consult with". I thought that if I found a company that met these conditions, I would be able to grow while being stimulated by those around me, so I narrowed down my options.
The appeal of DLTX during my job search was that the majority of my clients were Dai-ichi Life and Dai-ichi Life Group companies, so I could take the time to accumulate domain knowledge and build up personal connections, which I could then use in future projects. I was also very attracted by the fact that I could use the vast amount of data held by the Dai-ichi Life Group for analysis, and that there are various analysis needs. Another reason I decided to join the company was that I had a very good impression of the person I spoke to during the job interview.
To contribute to strengthening organizational and team strength
As I expected before joining the company, DLTX has many amazing people with a wealth of knowledge and skills around me. There are people at Dai-ichi Life and the Dai-ichi Life Group who are trusted experts in their fields, and I can rely on them to solve specific issues. It's an ideal environment to grow as a data scientist.
My future goal is to have strengths in data science, engineering, and business. For example, in data science, I would like to have a wealth of knowledge and skills related to AI, and in business, I would like to gain strengths such as being familiar with the corporate sales department.
Currently, I am in charge of training in the Data Strategy Office and manage study sessions within the department. Because of this position, I am actively working on obtaining qualifications as part of my knowledge and skill acquisition. Since joining the company, I have obtained qualifications such as the "Deep Learning for GENERAL : JDLA Certificate", an AI-related qualification, and the "Data Scientist Test", which certifies knowledge and skills in mathematics, data science, and AI. DLTX has a system in place to support qualification acquisition, so I would like to continue challenging myself to obtain more advanced qualifications. I am also taking the "Life Insurance Course", which evaluates my knowledge of insurance.
As I grow as a data scientist, I would like to continue engaging in activities that will ultimately lead to improved organizational and team strength.
