Managing daily reporting and deep-dives of critical OHL Opex workstreams. Working in a dynamic environment, you will be responsible for automating dashboards, monitoring key success metrics, managing WBR reports, identifying problem areas and business challenges and collaboratively shaping solutions with OHL Op Ex teams to help optimize on the platform. The successful candidate has a passion for extracting actionable insights from data. The candidate needs to innovate, and quickly become a subject matter expert to assess business performance across different OHL Opex areas. The candidate should have significant experience working with automation, analyzing data, identifying trends, extracting conclusions, and presenting findings in a simple and clear manner using data across various data marts, and align focus on Amazon’s strategic needs. The candidate should enjoy problem solving and is proficient in VBA and other automation tools. Co-ordinating with central stakeholders to maintain the data, queries and ensure right reporting. Minimum 12 months experience is as a BA is needed for this role.
Key job responsibilities

Key Responsibilities:

· Understanding drivers, impacts, and key influences in the Biz Ops Domain.
· Partnering with the business team to create key performance indicators and new methodologies for measurement.
· Translating data into actionable insights for the stakeholders.
· Automate reporting for weekly business metrics, identify areas of opportunity to automate and scale ad-hoc analyses
· You will perform complex data analysis (root cause deep dives, correlations, regressions, simulations, and optimization) to identify different opportunities to reduce process gaps.
·You will build infrastructure and implement maintenance strategy for internal datasets to support swift analysis to answer critical business questions

Basic Qualifications

• 1+ years of data analytics or automation experience
• 1+ years of capacity planning, operations planning, business analysis or similar experience
• Bachelor's degree
• Knowledge of data pipelining and extraction using SQL
• Knowledge of SQL and Excel at a moderate or advanced level
• Experience with data mining tools like SQL, SAS, SPSS, or similar

Preferred Qualifications

• Bachelor's degree in a quantitative discipline such as statistics, mathematics, economics, computer science, or any related quantitative field
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