Key Job Details:
- Compensation: Competitive Salary
- Position: Data Scientist
- Location: Remote
- Company: Amazon
- Start Date: Immediate openings available
We are seeking Information Science experts to drive our logical transformation within the Ability Securing (TA) space. This is a unique opportunity to lead a ground-up remake of our logical capabilities, encompassing everything from data ingestion to complex business changes, client detailing, and beyond. You will be instrumental in imagining and expanding our capabilities, testing innovative ideas, and ensuring consistency.
The ideal candidate is a resourceful Information Researcher capable of sourcing, cleaning, breaking down, refining, modeling, presenting, mechanizing, and archiving our business data pipelines. You will continuously identify opportunities to enhance the data stream process, stay abreast of the latest trends in data warehousing, and have the ability to manage and work on various related projects.
Key Responsibilities:
- Collaborate with specialists, software engineers, and business stakeholders to define business processes and provide analytical support.
- Leverage code to analyze complex datasets, create and evaluate data transformations to solve specific business problems.
- Develop adaptable, efficient, and automated data processes to support client-facing reporting.
- Automate TA processes to streamline business operations.
- Communicate verbally or in writing to business clients/stakeholders to share knowledge and insights.
Essential Qualifications:
- Bachelor's degree in a quantitative field (e.g., mathematics, statistics, data science, business analytics, economics, engineering, or computer science).
- 3+ years of experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), or statistical/programming languages (e.g., R, SAS, Matlab).
- 3+ years of experience with AI/statistical modeling data analysis tools and techniques, and boundaries that influence their application.
- Experience applying statistical models in a practical environment.
Preferred Qualifications:
- Master's degree in a quantitative field (e.g., mathematics, statistics, data science, business analytics, economics, engineering, or computer science).
- Experience in a Machine Learning or Data Science role within a large technology organization.
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