Data Scientist II, Data Scientist II

3 weeks ago

Dublin, Dublin City, Ireland Amazon Full time
Job Description
Are you interested in applying your strong quantitative analysis and big data skills to world-changing problems? Are you interested in driving the development of methods, models and systems for capacity planning, transportation and fulfillment network? If so, then this is the job for you.

Our team is responsible for creating core analytics tech capabilities, platforms development and data engineering. We develop scalable analytics applications and research modeling to optimize operation processes. We standardize and optimize data sources and visualization efforts across geographies, builds up and maintains the online BI services and data mart. You will work with professional software development managers, data engineers, scientists, business intelligence engineers and product managers using rigorous quantitative approaches to ensure high quality data tech products for our customers around the world, including India, Australia, Brazil, Mexico, Singapore and Middle East.

Amazon is growing rapidly and because we are driven by faster delivery to customers, a more efficient supply chain network, and lower cost of operations, our main focus is in the development of strategic models and automation tools fed by our massive amounts of available data. You will be responsible for building these models/tools that improve the economics of Amazon's worldwide fulfillment networks in emerging countries as Amazon increases the speed and decreases the cost to deliver products to customers. You will identify and evaluate opportunities to reduce variable costs by improving fulfillment center processes, transportation operations and scheduling, and the execution to operational plans. You will also improve the efficiency of capital investment by helping the fulfillment centers to improve storage utilization and the effective use of automation. Finally, you will help create the metrics to quantify improvements to the fulfillment costs (e.g., transportation and labor costs) resulting from the application of these optimization models and tools.

Major responsibilities include:

1. Translating business questions and concerns into specific analytical questions that can be answered with available data using BI tools; produce the required data when it is not available.
2. Apply Statistical and Machine Learning methods to specific business problems and data.
3. Create global standard metrics across regions and perform benchmark analysis.
4. Ensure data quality throughout all stages of acquisition and processing, including such areas as data sourcing/collection, ground truth generation, normalization, transformation, cross-lingual alignment/mapping, etc.
5. Communicate proposals and results in a clear manner backed by data and coupled with actionable conclusions to drive business decisions.
6. Collaborate with colleagues from multidisciplinary science, engineering and business backgrounds.
7. Develop efficient data querying and modeling infrastructure.
8. Manage your own process. Prioritize and execute on high impact projects, triage external requests, and ensure to deliver projects in time.
9. Utilizing code (Python, R, Scala, etc.) for analyzing data and building statistical models.

BASIC QUALIFICATIONS

- 2+ years of data scientist experience
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Experience applying theoretical models in an applied environment

PREFERRED QUALIFICATIONS

- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

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