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AI Engineer 1More

9M JPY - ***M JPY

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Tokyo

Full-time (permanent)

Online Interview: Yes

Remote Work from Overseas: Yes / Remote Work in Japan: No

Top-Selling Points

Rate of Foreigners

Less Than

Frequency of English Usage

Less Than

Related Skills

Experienced area / job

Big Data Deep Learning Machine Learning

Library/Framework

NumPy Pandas

Programming Language

Python

Data analysis / Machine learning

Tensorflow

Management/System project Experience

Others

Language Requirements

Required

Preferred

Job Description

The Group R&D Division provides technical support, development, and analysis for startups and cross-group projects that the company is focusing on in its business areas, and supports business success.

The AI R&D Office is included in this group, and provides support related to data analysis and AI. They are also constantly researching and developing the latest technologies, and are quick to introduce them into the business, leading to results.

You will participate in a joint research project on senescent cells with the Institute of Medical Science, The University of Tokyo.
In the field of single cell analysis, one of the hottest topics in bioinformatics (dry analysis), this project is a cutting-edge study of “senescent cells,” one of the hottest areas of research today.
Research that applies the latest generation AI foundation model (Foundation Model) and various machine learning techniques, and delves deeply into the nature of data and AI models to uncover the genetic mechanisms of senescent cells.

The AI R&D office also conducts a variety of business projects, and you can participate in other projects while doing collaborative research or afterwards, and develop your desired career based on your performance.

◆Fintech (Fintech) Projects
Understanding the nature of the financial services offered by the company group, and using data science techniques such as mathematical modeling and machine learning to successfully handle difficult-to-predict financial data and improve profitability.

◆Adtech (Adtech) projects
In RTB (Real Time Bidding), one of the main mechanisms of Internet advertising, we mainly design and develop machine learning models for DSP (Demand-Side Platform), which optimizes cost-effectiveness for advertisers, and measure its effectiveness.

◆App projects
Measuring the effectiveness of new features and measures for apps that facilitate free WiFi access, using causal inference techniques to improve the KPI of the service by setting up a system for data-driven management decision making.

◆Other projects
Support the application of data analysis and machine learning techniques with respect to crypto asset trading, fraud detection, etc.

【R&D work】
・While performing project work, all members will spend a certain amount of time researching cutting-edge machine learning methods and new machine learning applications.
・In addition, members appointed on a quarterly basis will conduct focused research and development.

【Attractiveness of this position】]
You can be involved in very challenging research using aging cells, one of the cutting edge of biology, and state-of-the-art AI technology, and contribute to the elucidation of unknown mechanisms of humankind!
You will constantly learn cutting-edge machine learning, deep learning, statistical methods, etc.
You can acquire three important skills (problem solving, data science, and engineering) and greatly develop one or more of your strengths.
You will have many opportunities to interact with data scientists from different departments who are in charge of different projects through study sessions and other opportunities to improve your data science skills.
As a department under the direct control of the group CTO, the selection of technologies is left to the field, so you will be able to verify and introduce cutting-edge technologies on your own.
Depending on your performance and motivation, you can take on the challenge of freely conducting research and development on the team's key themes.

In addition, if you are involved in projects other than aging cell research collaborations, you will have the following opportunities
Opportunities to launch projects from scratch to solve various issues through data analysis and AI technologies for the company group's diverse services.
You can directly handle a wide range of data, including the world's largest financial data and ad-tech data of several hundred terabytes, and learn techniques for analyzing big data (BigQuery, PySpark, etc.).
You can analyze various types of data such as time-series data, user behavior data, articles, etc.
Because all of the services are in-house, you will be able to work with the business unit to set up your own issues, think about how to solve them, and implement a cycle of improvement based on data science.
The team is diverse, consisting of people such as PhDs and engineers who have worked in academic fields.

【Technology used】
◆Analysis methods
Single cell RNA analysis, gene expression analysis
Machine learning:
Transformer systems (large-scale language models, single-cell generative AI models, etc.), graph neural networks (GNN), multilayer perceptrons (MLP), ensemble learning/gradient boosting (Gradient Boost Tree + LR, Random Forest, ExtraTree , Ada Boost, XGBoost, LightGBM), PCA, FP-Growth, Word2Growth ExtraTree , Ada Boost, XGBoost, LightGBM), PCA, FP-Growth, Word2Vec, Doc2Vec, collaborative filtering, Bayesian estimation, HMM models (hidden Markov models)
Statistical Analysis:
t-test, Chi-square test, F-test, binomial test, Kolmogorov-Smirnov test, Shapiro-Wilk test, sampling (MCMC, bootstrap method, etc.), analysis of variance, causal inference (difference in differences method)

◆Development techniques/environment
Programming/Frameworks
R, Python, PyData (numpy, scipy, pandas, etc.), Streamlit
PyTorch, TensorFlow, LangChain, Spark (PySpark)
Cloud/on-premise (middleware)
SHIROKANE
GPU workstation

Development tools
Atlassian (Jira, Confluence)
VS Code, PyCharm, Jupyter
GitHub (Copilot)
ChatGPT, Gemini, Claude

Development Methodology
Agile development (scrum-based)

Required Skills and Experiences

【Required】 Meet all of the following ・Experience in bioinformatics (dry analysis) research ・Have a PhD degree ・Knowledgeable in machine learning and deep learning ・Able to write R or Python 【Preferred】・Experience with biological wet lab research. 【Ideal Applicants】・Likes to consider all approaches to solving business problems and finding the best way to do it, rather than just using a method. ・Interested in and passionate about anything and everything, and able to take on new technologies and new tasks ・Able to work as a team to achieve great results that cannot be done alone ・Critical thinking, not just relying on data and results

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Working Condition

Defined contribution pension plan
Full social insurance (health insurance, welfare pension, defined benefit pension plan, unemployment insurance, workers' accident compensation insurance)
Employee Stock Ownership Plan
Welfare subsidy system (subsidies for sports clubs, English conversation, etc.)
Contracted recreational facilities
Commuting allowance (within tax exempt limit)
Car commuting system (only for Fukuoka work)
Condolence and sympathy payment
Childcare/nursing care leave and shortened working hours
Event subsidy system　
System to receive a part of salary in bitcoin
Excellent welfare facilities
　(24-hour free in-house cafe, massage room, nap space, day care center)
Enriched engineer support system

RECRUITMENT PROCESS

■Please expect the process from application to job offer to take approximately 3 to 4 weeks.

[Step 1] Application
　 ▼
[Step 2] Resume Screening
　 ▼
[Step 3] First Interview with Department Manager
　 ▼
[Step 4] Technical Test
　 ▼
[Step 5] Final Interview with Executive
　　▼
[Step 6] Job Offer

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