Analytics Insights Lead

Fluency in Japanese and business level English
- Bachelor’s degree with emphasis on statistical and analytical skills
- 7+ years of relevant experience
- Proficiency in relational databases (Redshift, RDS, SQL Server, MySQL, etc.) and SQL for querying and extracting data
- Proficiency in at least programming languages (Python, Java, R, etc.) for data gathering, data cleansing and statistical analysis

The APJ Sales Insights, Analytics & Data (Eng.) Science (APJ SIADS) team is one of the functions within the Global Sales Operations (GSO) team supporting the AWS Global Sales Asia Pacific and Japan (AGS APJ). It is the single source of truth (SSOT) for all data, reports, dashboards and metrics used to run the business in APJ.
**Our key priorities are**:
1) Modernize core data infrastructure and datasets to scale and support planned business growth;
2) Be custodians of data security by providing a secure platform for data and insights, which furnishes only the required set of accurate data (least privilege data access);
3) Move away from thinking about ad-hoc reporting as outcome and align towards insights products that deliver actionable guidance;
4) Make it easy for field teams to navigate to one version of truth; and
5) Leverage AI/ML models to help pinpoint timely insights and actionable recommendations.
Key job responsibilities
AIL(BI)s support over 2000 users in AGS APJ by creating insights products for self-service analysis and business critical publications for the APJ Leadership Team. They also develop datasets that are used for insights products, built on the data platform maintained by the Data Engineers. They ensure the standardization of datasets, guaranteeing that APJ SIADS products and publications are accurate, timely, accessible and aligned with the SMGS standardized definitions. As experts in data and business metrics, they guide the team in generating insights and reports using thousands of datasets from number of sources.
**Main responsibilities**:

- Lead the development of self-service reporting and analysis by creating and owning business reports and insight products
- Conduct data analysis to solve business problems through the use of statistical and/or machine learning models
- Continuously sharpen the skillset by learning and maintaining knowledge of existing and emerging business intelligence tools
- Collaborate with the internal and global data engineering teams on the design, development and maintenance of data infrastructure including data models
- Collaborate with the internal and worldwide data science teams on the design, development and maintenance of statistical and/or artificial intelligence/machine learning (AI/ML) models

About the team
Diverse Experiences
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
- Expertise in data visualisation software (QuickSight, Tableau, PowerBI, etc.) for effective data presentation
- Creative and analytical thinking to generate interesting approaches to answering business questions
- Strong and effective written and oral communication to clearly convey data findings
- Proficiency in different types of databases (relational vs. non-relational, etc.) and their relevant use cases
- Experience working with Cloud Computing
- Experience in deploying artificial intelligence/machine learning (AI/ML) models into production