坪井 利樹
Senior Data Scientist
Joined aiQ in September 2019
Expanded investment potential
with new data

SCHEDULEHow I spend a typical business day at aiQ

  • 09:00

    Take a seat at my desk and start working

    Check email and internal chat, prepare for work

  • 09:45

    Morning meeting

    Report the progress and today's work

  • 10:00

    Data analysis and investment strategy development

  • 12:00

    lunch break

  • 13:00

    Client Meetings

  • 14:00

    Meeting with Sales team

  • 14:30

    Meeting with Data Science team

  • 15:30

    Data analysis and investment strategy development

  • 18:30

    End of the work day

The ability to model financial products and forecast returns using data that is not yet widely used is a major attraction
How did you come to work at aiQ/what motivated you to apply for a new job?

My previous job was as an engineer in the quant department of a securities company. My boss at that time was aiQ's CEO Yuki Yamamoto, and when he founded aiQ he offered me a Data Scientist role. I had a longstanding interest in data analysis and machine learning as a personal hobby, making me keenly interested in this new position. At the time alternative data was an emerging field, which was a focal point for aiQ. The opportunity to tackle the challenge of modeling financial products and predicting returns using data not yet widely used motivated me to make a career change

Thinking about investment strategies is one of the most exciting aspects of daily work
How is it to work at aiQ?

My two main responsibilities at aiQ are data generation for aiQ’s POS datasets, and consulting services for institutional investors. In the aiQ POS data business, my responsibilities encompass data engineering and analysis. In data engineering, I manage POS and receipt data, performing tasks such as cleansing, formatting, and transforming the data into investment information. On the analysis front, I develop sales forecasting models for listed companies and generate client reports based on the outcomes. The tangible results of these efforts provide a clear sense of accomplishment, making each task rewarding. In my consulting role for institutional investors, I am mainly responsible for evaluating new data sets, as well as proposing and implementing investment strategies. The daily exposure to new data is one of the most thrilling aspects of being a data scientist. Simultaneously, crafting investment strategies by leveraging aiQ's domain expertise, machine learning techniques, and adept data handling skills is one of the most exciting aspects of my daily responsibilities. Furthermore, the most attractive characteristic of aiQ is the expertise of its team members. A cadre of specialists spanning quant, machine learning, derivatives, risk management, ML engineers, and infrastructure engineers collaboratively pool their knowledge to propel projects forward. The flat organisational structure unique to a venture company is also an attractive feature, allowing for very quick decision-making and direct communication with the necessary information and people. In addition, the company’s foundation on remote working enables flexible work arrangements, taking into account childcare and family circumstances. Thanks to this environment I am able to maintain a strong work-life balance

We want to promote the alternative data we provide
What challenges do you want to take on at aiQ in the future?

The first thing we would like to do in the future at aiQ is to expand our data analysis business. We would like to promote the spread of alternative data that we provide. We also believe that there is a great deal of data around the world that is not well maintained but can be used for investment. We would like to develop and evaluate them to further expand investment possibilities. In our consulting business, we would also like to propose optimal investment strategies that meet our clients' needs while keeping up with the latest machine learning technology and financial knowledge.
As for my personal goals, up until now I have focused on analysing individual Japanese stocks, but in the future I would like to work on analysing other asset classes such as foreign stocks, currency exchange, and commodities. In addition, I have recently become increasingly interested in team management. Until now, my role has been mainly as a player, but I feel it is essential to expand the team and develop its members in order to further scale the work, and I would like to focus on this aspect as well

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