AddressAre you a talented and inventive scientist with a strong passion about modern data technologies and interested to improve business processes, extracting value from the data? Would you like to be a part of an organization that is aiming to use self-learning technology to process data in order to support the management of the procurement function?
The Global Procurement Technology, as a part of Global Procurement Operations, is seeking a skilled Data Scientist to help build its future data intelligence in business ecosystem, working with large distributed systems of data and providing Machine Learning (ML) and Predictive Modeling expertise. You will be a member of the Data Engineering and ML Team, joining a fast-growing global organization, with a great vision to transform the Procurement field, and become the role model in the market. This team plays a strategic role supporting the core Procurement business domains as well as it is the cornerstone of any transformation and innovation initiative. Our mission is to provide a high-quality data environment to facilitate process optimization and business digitalization, on a global scale. We are supporting business initiatives, including but not limited to, strategic supplier sourcing (e.g. contracting, negotiation, spend analysis, market research, etc.), order management, supplier performance, etc.
We are seeking an individual who can thrive in a fast-paced work environment, be collaborative and share knowledge and experience with his colleagues. You are expected to deliver results, but at the same time have fun with your teammates and enjoy working in the company. In Amazon, you will find all the resources required to learn new skills, grow your career, and become a better professional. You will connect with world leaders in your field and you will be tackling Data Science challenges to ensure business continuity, by taking the right decisions for your customers.
As a Data Scientist in the team, you will:
- be the subject matter expert to support team strategies that will take Global Procurement Operations towards world-class predictive maintenance practices and processes, driving more effective procurement functions, e.g. supplier segmentation, negotiations, shipping supplies volume forecast, spend management, etc.
- have strong analytical skills and excel in the design, creation, management, and enterprise use of large data sets, combining raw data from different sources
- provide technical expertise to support the development of ML models to facilitate intelligent digital services, such as Contract Lifecycle Management (CLM) and Negotiations platform
- cooperate closely with different groups of stakeholders, e.g. data/software engineers, product/program managers, analysts, senior leadership, etc. to evaluate business needs and objectives to set up the best data management environment
- create and share with audiences of varying levels technical papers and presentations
- deal with ambiguity, prioritizing needs, and delivering results in a dynamic environment
Basic Qualifications
Master’s Degree in Computer Science/Engineering, Informatics, Mathematics, or a related technical discipline
4+ years of industry experience in data engineering/science, business intelligence or related field
4+ year experience in algorithm design, engineering and implementation for very-large scale applications to solve real problems
Very good knowledge of data modeling and evaluation
Very good understanding of regression modeling, forecasting techniques, time series analysis, machine-learning concepts such as supervised and unsupervised learning, classification, random forest, etc.
Track record of developing and applying ML models to business problems (Procurement, Transportation, Finance, etc.)
Advanced SQL level and query performance tuning skills
3+ years of proficiency in using R, Python, Scala, Java or any modern language for data processing and statistical analysis
Preferred Qualifications
PhD in ML & Data Science, Applied Data Science, Web Science, Statistics, Analytics, or a related discipline
Experienced in applying theoretical models in an applied environment
Experience with various RDBMS, such as PostgreSQL, MS SQL Server, MySQL, etc.
Experience architecting Big Data and ML solutions with AWS products (Redshift, DynamoDB, Lambda, S3, EMR, SageMaker, Lex, Kendra, Forecast etc.)
Experience articulating business questions and using quantitative techniques to arrive at a solution using available data
Experience with agile/scrum methodologies and its benefits of managing projects efficiently and delivering results iteratively
