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 strategy 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.
We are looking for experienced hands-on Manager of Data Science to join us and lead science programs and developments for Amazon global.
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 analytics tech services and applications 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.
Major responsibilities of the team include:
· Translating business questions and concerns into specific analytical questions that can be answered with available data using statistical methods.
· Apply Statistical and Machine Learning methods to specific business problems and data.
· 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.
· Communicate proposals and results in a clear manner backed by data and coupled with actionable conclusions to drive business decisions.
· Collaborate with colleagues from multidisciplinary science, engineering and business backgrounds.
· Work with engineers to develop efficient data querying and modeling infrastructure.
· Manage your own process. Prioritize and execute on high impact projects, triage external requests, and ensure to deliver projects in time.
· Utilizing code (Python, R, Scala, etc.) for analyzing data and building statistical models.
· Masters in quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent).
· 8+ years of experience working in data science ideally in the tech or consumer industry.
· 5+ years of experience managing Machine Learning Scientists, Data Scientists, Research Scientists, Applied Scientists, and/or Economists.
· Evidence of doing or directing science work with high positive impact on business outcomes.
· Experience hiring and leading experienced scientists as well as a successful record of developing junior members to a successful career track.
· Management experience for working on cross-functional projects.
· Proven achievements of developing and managing a long-term research vision and portfolio of research initiatives, that have been successfully integrated in production systems or informed policy decisions.
· Proficient with SQL and at least one scripting language (e.g., R, Python).
· Demonstrable expertise in research design methodologies (e.g., experiments, quasi-experiments, surveys, sampling methods, etc).
· A PhD in a quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent)
· 10+ years of experience working in data science
· 7+ years of experience managing Machine Learning Scientists, Data Scientists, Research Scientists, Applied Scientists, and/or Economists
· 4+ years of experience managing data scientists skilled with languages such as R, MATLAB, Python or others
· Superior verbal and written communication skills, ability to convey rigorous mathematical and statistical concepts and considerations to non-experts.
· Experience with AWS technologies like Redshift, S3, Sagemaker, EC2, Data Pipeline, & EMR.
· Publications or presentation in recognized Machine Learning or Statistical journals/conferences.
· Strong organizational skills, time management, and program management skills.