We are seeking a highly analytical, technically strong professional with deep expertise in coding and Machine Learning to identify, design and deploy advanced analytics that identify process improvements, unlock growth opportunities, and enhance operational efficiency across Amazon. This role will leverage advanced data analytics to uncover insights from complex datasets and translate them into scalable, actionable solutions that directly impact business performance.

• Key job responsibilities
• Define and own analytical and Machine Learning problem statements that address process gaps, efficiency bottlenecks, and revenue opportunities.
• Apply advanced analytics to interpret complex, large-scale datasets and uncover actionable insights that inform Business Development strategy and execution.
• Design scalable, data-driven solutions to improve end-to-end Business Development workflows, from opportunity identification through project prioritization and revenue realization.
• Partner cross-functionally with partner teams to align analytical initiatives with business priorities and measurable outcomes.
• Drive technical rigor and best practices in coding, modeling, and data validation to ensure accuracy, scalability, and long-term maintainability of solutions.
• Develop analytical and Machine Learning models that detect process inefficiencies, operational risks, and optimization opportunities.

About the team
Finance and Global Business Services (FGBS) Amazon Customer excellence systems (ACES) team applies Lean Six Sigma problem-solving skills to improve Amazon processes, align them with customer requirements, and deliver positive effects in controllership and cost savings. The Business Development team contributes by developing cross-organizational partnerships to drive identification, quantification, and definition of project opportunities between FGBS verticals and ACES Black Belts. We are a project discovery task force that specializes in linking business strategy to opportunity identification and project selection. The business development strategy uses a combination of voice of the customer, voice of the business, voice of the employee, and voice of the process to capture improvement opportunities in complex interdependent business functions. We believe the future of successful project management involves doing the right projects—not just doing projects right. That means making excellent decisions about which opportunities should become projects. This role applies a mixture of Qualitative, quantitative, networking and leadership skills to drive a culture of exploration, opportunity creation, and continuous improvement. This role has a documented track record of leading, building rapport, and mentoring process improvement teams comprising members of all levels and functions without formal reporting relationships.

Basic Qualifications

• 3+ years of program or project management experience
• Bachelor’s degree in computer science, Engineering, Statistics, Mathematics, or a related quantitative field.
• Strong analytical mindset with demonstrated ability to solve ambiguous business problems using data
• High proficiency in Python and SQL
• Hands-on experience with Machine Learning techniques such as regression, classification, clustering, anomaly detection, and time-series analysis
• Experience working with large-scale datasets and applying statistical methods to derive insights
• Proven ability to handle confidential information appropriately
• Proficient in obtaining, organizing, and analyzing data to make fact-based decisions and drive root cause analysis
• Be comfortable with ambiguity and curious to learn new skills
• History of collaboration, critical thinking and problem solving

Preferred Qualifications

• Experience building processes, project management, and schedules
• Master’s in computer science and engineering
• 3+ years of experience in analytical field
• Proven proficiency in SQL for data extraction and manipulation
• Strong programming skills in Python, with experience in libraries such as Pandas, Num Py, and Sci Py for data analysis
• Demonstrated subject expertise in transactional data analysis

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