Principal Data Scientist

必須

• 次のいずれか

  • Bachelor's degree in data science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • master's degree in data science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• Business-level or higher proficiency in both Japanese and English is required.

• 次のいずれか

  • Bachelor's degree in data science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 12+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • master's degree in data science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 8+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)

使用ツール

Business Understanding and Impact

• problems and issues facing projects to uncover, manage, and/or mitigate factors that can influence final outcomes across product lines.
• Partners with business in specialized areas by staying abreast of current and emerging methodologies an AI and ML.

Evaluation

• Conducts thorough review of data analysis and modeling techniques used to summarize the process review and highlight areas that have been missed or need reexamining.
• Utilizes results of the assessment and process review to decide on next steps (e.g., deployment, further iterations, new projects).
• Identifies new evaluation approaches and metrics and invents new methodologies to evaluate models.
• Tracks advances in industry and academia, identifies relevant state-of-the-art research, and adapts algorithms and/or techniques to drive innovation and develop new solutions.
• Researches and maintains deep knowledge of industry trends, technologies, and advances.
• Leverages knowledge of work being done on team to propose collaboration efforts.
• Proactively develops strategic responses to specific market strengths, weaknesses, opportunities, threats, and/or trends.
• Mentors and coaches less
• Serves as subject matter expert and role model for less experienced engineers.
• Identifies strategy opportunities.
• Actively contributes to the body of thought leadership and intellectual property (IP) best practices by actively participating in external conferences.

Coding and Debugging

• Independently writes efficient, readable, extensible code/model that spans multiple features/solutions.
• Contributes to the code/model review process by providing feedback and suggestions for implementation and improvement.
• and/or debugging techniques such as locating, isolating, and resolving errors and/or defects.
• Leads a project team in the gathering, integrating, and interpreting of data/information from multiple sources in order to properly troubleshoot errors.
• partnerships between product teams, Sales teams, Area teams, and Services.
• Work collaboratively across disciplines.
• Leads involvement of intellectual property (IP) definition improvement.

Customer/Partner Orientation

• Commits to a customer-oriented focus by acknowledging customer needs and perspectives, validating customer perspectives, focusing on broader customer organization/context, and serving as a trusted advisor.
• Identifies opportunities and adds valuable insight by incorporating an understanding of the business, product/service functionality, data sources, methodologies to reframe problems, and the customer perspective.
• Interprets results, develops insights, and effectively communicates results to the customer.
• Leads the discussion with customers and offers pragmatic solutions that are feasible given their data limitations.