募集要項
- 募集背景
- The company has just openeded an entirely new DX department, they are looking for senior members to lead it and be involved in the formation of an exciting new space.
- 仕事内容
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Looking for a data expert with experience in data science and/or machine learning to work on global proejcts and cutting edge technologyThe Data Expert is at the core of designing, building, and deploying value-driven digital applications. The Deployment Engineer is part of the technical core team alongside the Deployment Strategist and maintains close relationships with customers to get the job done. The Deployment Engineer is responsible for finding problems and writing code to create valuable applications. To do this, you will need to have strong problem-solving skills, extensive knowledge of digital technologies, and expertise in a specific area. Thus, in this case, the area of expertise is application analysis and data science.
The work in this role is not routine in nature. Expected activities during customer interactions include
- Working with customers to identify problems and lead value identification on-site.
- Develop and implement strategies to solve problems in a variety of ways.
- Build end-to-end workflows for data, including cleaning, wrangling, analysis, machine learning, and visualization.
- Lead the technical implementation of each project, translating product vision and customer needs into development tasks.
- Focus on own value creation and maximize value to the system being built.
- Deploy projects with end-users and gather feedback, bugs, etc.
- 応募資格
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- 必須
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Analytical/Data Scientist Skills:
- Operating within agile software development (Scrum, SAFe, Kanban, etc.).
- Advanced programming skills in Python: 5+ years of experience, especially in data science applications and workflows.
- Experience in data wrangling and modeling: must have sufficient knowledge of how to create data pipelines, integrate multiple structured and unstructured data sources, perform feature engineering, and have the ability to facilitate downstream analysis and visualization. (Must have experience with Pandas, SQL, NoSQL, PySpark, and RegEx.)
- Statistics: must have experience applying statistical methods to real-world projects.
- Traditional machine learning: Supervised learning (e.g. logistic regression, random forests, SVMs) and unsupervised learning (e.g. clustering methods, manifold methods). Experience implementing SciKit Learn (SKlearn) or similar packages.
- Data Visualization: must have experience in building compelling data visualizations. Must have experience with packages such as Matplotlib, ggplot, bokeh, plotly, dash, etc. Must also be able to use dashboard tools such as spotfire, tableau, PowerBI.
- 歓迎
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- Deep Learning [Preferred but not required]: knowledge of various neural network architectures such as all-junction layer, convolutional, iterative, LSTM, Deep-Q, etc. and the correct applications. frameworks such as TensorFlow, PyTorch, etc. Must be able to use.
- Expertise in more advanced analysis [preferred but not required]: optimization methods (convex, linear, nonlinear, genetic, multimodal, multi-factor, etc.), time series analysis (signal processing, spectral analysis, time warping, Kalman filter, FFT, time series feature engineering, etc.)
- 雇用形態
- Active
- 勤務地
- Tokyo
- 年収・給与
- 9.5 million yen ～ 12.49 million yen
