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Data Analyst 993 views

The ideal candidate will have excellent analytical abilities, strong technical skills, outstanding business acumen, intense curiosity, and superior verbal/written communication skills. The successful candidate will be a self-starter that is comfortable with ambiguity, strong attention to detail, and an ability to work in a fast-paced and ever-changing environment. Experience in Amazon systems and processes will be a key enabler of your success.

They are looking for someone with a track record of data-driven root cause analysis (Deep Dive), an ability to innovate (Invent and Simplify), can operate comfortably in a fast-paced environment (Bias for Action), and has an ability to work with ambiguity across disparate business and technical teams (Earns Trust).

Basic Qualifications

  • Degree in Computer Science, Engineering, Statistics, or Economics.
  • 5+ years of relevant work experience in data science, business intelligence, or other big data environments.
  • Strong proficiency at querying relational databases, eg. Oracle SQL Developer, ETL, Redshift, Vertica, MS SQL.
  • Proficient in multiple flavors of SQL, (e.g. PostgreSQL, MySQL, Redshift)
  • Experience in data visualization platforms (e.g. Tableau, PowerBI, QuickSight)
  • Advanced Microsoft Office skills, particularly Excel (VBA) and analytical platforms.
  • Ability to prioritize multiple concurrent projects while still delivering timely and accurate results
  • Experience with big data: processing, filtering, and presenting large quantities (millions of rows) of data.
  • Ability to work effectively with Data Engineers to mine the correct data sources efficiently and accurately
  • Strong verbal/written communication and data presentation skills, including an ability to effectively communicate with both business and technical teams.
  • Genuine curiosity, proven problem-solving ability, and passion for data.

Preferred Qualifications

  • Experience in predictive modeling and analysis in big data environments.
  • Experience leading large-scale data warehousing and analytics projects, including using AWS technologies – Redshift, S3, EC2, Data-pipeline, and other big data technologies
  • Experience in advanced machine-learning methodologies (e.g. supervised and unsupervised learning, deep learning, etc.)
  • Experience with clustered data processing (e.g. Hadoop, Spark, Map-reduce, Hive)
  • Experience in one of the modern visualization/reporting tools such as Tableau, QuickSight, etc.
  • Experience using one or more programming languages (e.g. Python, Java, C++, C#, Ruby)

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