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ADCI PNQ | Jobs | Sr Business Intelligence Engineer, Zappos Analytics | BigDataKB.com | 01-04-22

Job Location: Pune

• 6+ years of strong quantitative and qualitative experience in Logistics/Supply Chain, Transportation, Engineering or Business experience
• Bachelor’s Degree in Engineering, Math, Statistics, Finance, Computer Science, or related industry experience
• Experience with statistical analysis, regression modeling and forecasting, time series analysis, data mining, financial analysis, and demand modeling
• Proficiency with Tableau, Microsoft Excel to include making charts, data manipulation, pivot tables, creating macros, and visual basic knowledge
• Able to write SQL scripts for analysis and reporting ( SQL, MySQL)
• Experience using one or more programming languages – Python, VBA, MATLAB, Java, C++ programming languages
• Experience processing, filtering, and presenting large quantities (100K to Millions of rows) of data

Job summary
You are self-motivated. You think like an entrepreneur, constantly innovating and driving positive change, but more importantly, you consistently deliver mind-boggling results. A role at Zappos is an opportunity to be a part of something different. To go bold. We’re a organization that isn’t afraid to take risks and question the status quo. Oh yeah, we like to have fun too. This position offers exceptional opportunities for every candidate to grow their technical and non-technical skills. If you are selected, you have the opportunity to really make a difference to our business by inventing, enhancing and building world class systems, delivering results, working on exciting and challenging projects.
Zappos Machine Intelligence/Analytics team seeks an experienced and motivated Data Scientist/Business Intelligence Engineer/Business Analyst with outstanding leadership skills, proven ability to develop, enhance, automate, and manage analytics models using strong quantitative skills. The successful candidate will have strong data mining and modeling skills and is comfortable facilitating ideation and working from concept through to execution. This role will also build tools and support structures needed to analyze data, dive deep into data to determine root cause of forecast/buying systems errors & changes, and present findings to business partners to drive improvements.
A qualified candidate must have demonstrated ability to manage medium-scale modeling projects, identify requirements and build methodology and tools that are statistically grounded but also explainable operationally, apply technical skills allowing the models to adapt to changing attributes. In addition to the modeling and technical skills, possess strong written and verbal communication skills, strong focus on customers and professional demeanor and high intellectual curiosity with ability to learn new concepts/frameworks, algorithms and technology rapidly as changes arise.
Additional responsibilities may include:

  • Research machine learning algorithms and implement by tailoring to particular business needs and tested on large datasets.
  • Manipulating/mining data from database tables (Redshift, Oracle, Data Warehouse)
  • Create automated metrics using complex databases
  • Providing analytical network support to improve quality and standard work results
  • Root cause research to identify process breakdowns within departments and providing data through use of various skill sets to find solutions to breakdown
  • Foster culture of continuous engineering improvement through mentoring, feedback, and metrics

• Master’s degree or higher in Engineering, Math, Finance, Statistics, Computer Science, or other technical field from an accredited university
• Excellent written and verbal communication skills. The role requires effective communication with colleagues from machine learning, economics and business backgrounds
• Experience working in a fast-paced, high tech environment (preferably software development) – Experience working in or with a complex international supply chain management organization
• Demonstrated experience incubating and commercializing new ideas, working closely with product managers, research scientists and technical teams from concept generation through implementation

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