Process Improvement Specialist, Central Flow

Description

About Japan Central Flow (JPCF) - RiCO Team

The RiCO (Risk & Capacity Optimization) team drives data-powered operational excellence across Japan's fulfillment network. We sit at the intersection of Central Flow, FC Operations, Finance, and Capacity Planning - using advanced analytics, BI tools, and automation to manage delivery speed (GVS), cost efficiency (UPB), and fulfillment reliability at scale.

What We Do:

BI & Analytics Experts: We build and maintain real-time dashboards, predictive models, and automated reporting solutions (QuickSight, Python, SQL) that enable data-driven decision-making across the network. We translate complex operational data into clear, actionable insights.

Capacity Optimization: We support Operations capacity planning from processing risk mitigation to speed optimization, identifying actionable opportunities in delivery performance and cost savings.

Process Innovation: We design, pilot, and scale solutions that reduce risk, increase speed, and drive efficiency. From automated alert systems to AI-enabled predictive risk models, we build the tools and frameworks that keep Japan's fulfillment network running at peak performance.

Cross-Functional Collaboration: We partner with Fulfilment Operations, Finance, Capacity Planning and global technology teams to implement best-in-class products and processes.

Why It Matters:

At Amazon, every day is "Day One." Our team embodies that mindset by continuously pushing the boundaries of what's possible in fulfillment operations.

We're in the middle of a multi-year transformation, moving from reactive problem-solving to proactive, intelligence-driven operations. Our work directly impacts how fast customers receive their orders, how efficiently our network operates, and how effectively we manage cost. When we build a better dashboard, automate a manual process, or uncover a root cause that's been hidden in the data, the result is millions of packages delivered faster and more reliably.

This is a team where your analytical work doesn't sit in a report, it drives real operational decisions, changes how fulfillment centers run, and shapes the strategic direction of one of Amazon's fastest-evolving logistics networks.

Your Role:

We're seeking a BI-oriented Process Improvement Specialist to own the design, development, and scaling of analytical solutions and process improvements that directly impact out key KPIs. You'll combine deep BI skills with operational acumen to build dashboards, automate reporting pipelines, perform root cause analysis, and drive multi-million-dollar capacity optimization initiatives.

Key job responsibilities

BI & Data Analytics (Primary Focus)

- Design, build, and maintain real-time dashboards and automated reporting solutions using QuickSight, SQL, Python, and Excel to track operational KPIs across Japan's fulfillment network.

- Develop data pipelines that replace manual processes, enabling scalable reporting and capacity scenario analysis at the required granularity.

- Perform root cause analysis to quantify performance gaps and prioritize improvement opportunities.

- Support the development of predictive models and forward-looking tools as part of the team's AI/ML roadmap.

Process Improvement & Optimization

- Own medium-to-large initiatives from ideation through implementation, building clear business cases with quantified impact and ROI.

- Design pilot programs, validate results with statistical rigor, and scale solutions across the network.

Collaboration & Stakeholder Management

- Partner with Operations, Planning, Finance, and international technology teams to align analytics with execution.

- Translate complex data into clear narratives for senior leaders and facilitate data-driven decision-making.

Automation & Continuous Improvement

- Build Python/SQL automation tools to reduce manual effort and improve reporting accuracy.

- Deepen operational understanding to ensure analytics solutions reflect real-world fulfillment processes.

Basic qualifications

- Speak, write, and read fluently in English

- Knowledge of BI analytics, reporting or visualization tools like Tableau, AWS QuickSight, Cognos or other third-party tools

- Experience with automation or working with scripting languages like Python, Java, Perl, PHP, Ruby, Bash, Shell, or equivalent

- 4+ years of defining and implementing process improvement initiatives using data and metrics experience

- Experience in project management including resource planning, managing schedules, reporting project status and prioritizing own tasks and those of other team members for multiple projects

- Bachelor's degree in Math, Engineering, Science or Business or 4+ years of experience in business intelligence, data analytics, or process improvement within operations/supply chain

Preferred qualifications

- Speak, write, and read fluently in Japanese

- Experience in program management, logistics, operations, supply chain, transportation, or equivalent

- Experience with the AWS platform, web services, software development, or related technologie

- Experience working cross-functionally and across regions

- Advanced Python skills including data pipeline development, automated reporting, and statistical analysis

- Familiarity with Infrastructure-as-Code concepts for deploying and managing analytical solutions

- Experience working with NoSQL databases (e.g., DynamoDB, document stores) for operational data management

- Experience building predictive models or working with ML/AI tools

- Familiarity with capacity planning, demand forecasting, or risk management frameworks

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.