Company and Position Overview
A leading global biopharmaceutical company is looking to hire a Data Scientist to join their exciting and fast paced team.
They are seeking Data Scientists to work closely with cross-functional business teams, adopting agile ways of working, to create business value and outcomes with data and Advanced Data Analytics.
Primary Job Responsibilities Include:
- Using Pyspark technology to improve a large amount of data such as 100 x 1 million rows and build a new model or improve an existing mathematical model using Sagemaker notebook in an AWS environment.
- Build and improve models on your own.
- Complete unanswered questions with team members without giving up.
【会社概要 | Company Details】
A world leader in the healthcare industry. The company strives to provide employees the opportunity to deliver the best medicines to patients in Japan and healthcare workers, under the mission "to save people's lives and improve their lives through innovative products and services."
【就業時間 | Working Hours】
8:45am – 5:30pm (with 1hr break), M-F, Flexibility required
【休日休暇 | Holidays】
Saturday, Sunday, and National Holidays, Year-end and New Year Holidays, Paid Holidays, Other Special Holidays
【待遇・福利厚生 | Services / Benefits】※スキルハウスベネフィット適応
Social insurance, Transportation Fee, Skillhouse Benefit
-Experience in summarizing his/her own analytical processes and results in a PowerPoint, by using diagrams, charts, etc., and explaining them to people with limited knowledge of Data Science.
- Experience in making presentations for Directors and/or Senior Management.
<Flexibility and Adaptability>
- Experience in working in an uncertain environment, where various tasks are required to be performed simultaneously.
- Experience in completing a project, even though the direction of the project changed significantly and multiple times, due to feedback from business stakeholders.
- Experience in modifying the predictive model in a speedy manner, to incorporate important, additional business requirements, even if such a modification may result into a model which is not the best from a Data Science point of view.
- Solving problems for which there is no clear answer.
- Ability to translate abstract problems from business owners into concrete issues to solve, to enumerate elements toward goals, and to derive satisfactory outcome.
<Ownership and Accountability>
- Appropriately handle pre-processing, but not just do the relatively fun parts for Data Scientists, such as model building and interpretation.
- Check and report the reliability of input data and delivered analytical results through intensive tests by him/herself.
<Problem Solving Skills>
- Not just find and report issues in his/her own work, but also articulate causes for them (e.g., pre-processing fault, lack of business understanding, mismatch in versions of Python libraries used, etc.), and propose how to deal with them.
- Ability to divide his/her own work into tasks and explain them clearly in daily meetings.
- Strong Python coding experience (as a Data Scientist, but not an IT Developer)
- Perform data manipulation using libraries such as Numpy, Pandas, Matplotlib, Seaborn, etc.
- Organize and simplify complex processes by creating scripts for functions and classes.
- Ability to handle errors.
- Experience in pre-processing large datasets, such as tabular data with 1,000,000 rows x 100 columns, and calculating basic statistics.
- Mathematical knowledge that is used in Data Science (calculus, linear algebra, equivalent to Japan Statistical Society Certificate level 2).
- 2+ years of experience as a Data Scientist.
- Experience, as a consultant of clients, in making presentation for Directors and/or Senior Management.
- Native level of fluency both in Japanese and in English.
- Experience in Agile Development.
- Experience in writing distributed processing in PySpark for Big Data Analytics solutions.
- Experience in Natural Language Processing (e.g., morphological analysis using MeCab, managing projects using BERT with Japanese data).
- Experience in Deep Learning frameworks (e.g., TensorFlow, PyTorch).
- Experience in building recommendation engine models (e.g., collaborative filtering, cosine similarity calculation, matrix factorization models).
- Experience in using and implementing the following modules in Data Science projects, to run models on a regular basis in an Amazon Web Service (AWS) environment.
- Amazon Sage Maker, Glue and Step Functions.
- 5+ years of experience as a Data Scientist.