Data Scientist (NLP and Search)

Job Type
Permanent
Salary
6,000,000 JPY ~ 9,000,000 JPY per year
Japanese Level
None
English Level
Advanced (TOEIC 860)
Start Date
ASAP
Location
Tokyo

Description

In the Data Intelligence Office we have professionals in various fields: Physics, Econometrics, Computer Science and Statistics. Collaborating with each other, we aim to maximize the business performance. We are looking forward to working with professionals in different fields as a member of the team.

 

We are looking for a highly motivated data scientist as a member of Data Intelligence Office. Activities of Data Intelligence Office consist of

(1) identification of business issues,

(2) algorithm development,

(3) online evaluation (e.g., AB testing), and

(4) system development.

 

【Responsibilities】

As a data scientist in NLP and Search;

- You will design and implement new search features by leveraging the latest technologies in machine learning and deep learning.

- You will participate in the development of various products related to search including keyword search and search word suggestion.

- You will also be the expert to solve NLP related problems such as named entity recognition, sequence completion, and user intent classification.

 

Besides problem solving with data scientist knowledge;

- You will also work on improving our machine learning pipeline in both Google Cloud Platform and internal system.

- You will solve real world data engineering problems including training operationalization, model serving for online prediction, data and feature management, and model version control.

 

【会社概要 | Company Details】
グローバルに展開する一部上場インターネットサービス企業です。様々な事業を展開し、成長を続けています。日本にいながら異文化コミュニケーションができる国際的な環境かつ、女性や外国籍の管理職登用にも積極的なダイバーシティな環境でもあります。世界的にも知名度アップを図り、スポーツチームのスポンサーなども積極的に行っています。
エンジニアの方には嬉しい、WindowかMacを自分で選択することができます!社内カフェテリアは明るく、毎日食べても飽きないほど、メニューが豊富です!
スキルハウスから就業しているスタッフも多く、年間成約数もトップレベルを誇ります。会社同士の信頼関係も厚く、面接のプロセスもスムーズです。実際に企業に応募する前に、経験豊富な企業の専任担当より会社の様子など、詳しくお伝えいたします。また、日本語・英語でのレジュメの書き方のアドバイスや面接の準備もいたします。ケースbyケースですが、社内ツアーを設定することもできます。

Our client is a large global Internet service company that has enjoyed sustained growth as they continue to expand their business in various new areas and industries. This is a great opportunity to work in a diverse and international environment in Japan. Our client actively strives to be an equal opportunity employer, and they have many female and foreign nationals in upper management positions. Their brand has also gained global recognition as they sponsor some of the world's most famous sports teams. Our client prides themselves in providing a comfortable working environment for their employees. Engineers are welcome to choose their own setup (Windows/Mac, etc.); whatever makes them comfortable! Free meals are also provided at the company cafeteria. Their chefs work to create exciting new menus and dishes, so employees never get tired of the food!
 
【就業時間 | Working Hours】
Flex (7.5 hours a day with core time 11:00-15:00)
 
【休日休暇 | Holidays】
完全週休2日制(土日祝休み)、年末年始、年次有給休暇、その他特別休暇など
Saturday, Sunday, and National Holidays, Year-end and New Year Holidays, Paid Holidays, Other Special Holidays
 
【待遇・福利厚生 | Services / Benefits】
各種社会保険完備(厚生年金保険、健康保険、労災保険、雇用保険)、 屋内原則禁煙(屋外に喫煙所あり)、 通勤交通費支給等
Social insurance, Transportation Fee, No smoking indoors allowed (Designated smoking area), etc.

 

Required Skills

- Firm understanding in machine learning and deep learning algorithms. Preferably having experience on natural language processing and information retrieval.

- Strong data engineer skills. Familiar with REST API design. Knowledge in building services on cloud platform. Knowledge in both SQL and NoSQL database.

- Fluent in Python. Knowledge on libraries including Tensorflow/PyTorch, Scikit-- Learn Pandas, and Flask/FastAPI.

Preferred Skills

- Experiences in developing deep learning model for recommendation system and learning to rank tasks. Understand the internals of the related loss functions and evaluation metrics.

- Knowledge in MLOps. Experiences in building machine learning pipeline with tools like Kubeflow and model serving in production.

- Experiences in building search engines with Elasticsearch.

- Knowledge in running online experiments with Bandit algorithm. Have working knowledge to design and conduct an AB test experiment, analyze the results, and convert them into business insights.

- Contributions to open source software development.