At Amazon, we strive to be the most innovative and customer centric company on the planet. Come work with us to develop innovative Customer Fulfilment products, tools and research driven solutions in a fast-paced environment by collaborating with smart and passionate leaders, program managers, data scientists and software developers. Our mission is to build the most efficient, intelligent and interpretable solutions on the planet.
The EU Ops Integration Analytics team is part of Amazon EU Customer Fulfillment and is responsible for improving and supporting performance management of our Fulfilment Centers through state-of-the-art and scalable analytics solutions. We work backwards from the customer and define new innovative solutions that raise the bar on customer experience whilst constantly lowering our cost and supporting our continued growth.
We are looking for a thought leader and you demonstrate this by delivering solutions, not just by having ideas. We encourage you to shape the business with data driven recommendations. A successful candidate has an entrepreneurial spirit and wants to make a big impact. You will develop strong working relationships and thrive in a collaborative team environment. Your role requires the ability to influence and interact with broad range of stakeholders (technical and non-technical). You draw from a broad data science expertise to mentor Data Scientists and Business Intelligence Engineers; following a rigorous scientific methodology, while providing leadership on complex analytical topics. You provide guidance on cutting-edge methods in big data processing, data science literature, experimentation and careful consideration of modeling decisions. We expect you to have breadth of data science knowledge, and depth in predictive modeling (supervised learning) and unsupervised learning (clustering).
· Develop predictive models and decision science to guide program and operations teams on improving our customer experience (e.g. predicting concessions and optimizing the best action to take, sustainability and energy etc.)
· Drive data science best practices and mentoring junior team members based on your in-depth knowledge in theoretical and practical data science disciplines.
· Proactively seek to identify business opportunities and provide solutions based on a broad and deep knowledge of Amazon’s data resources, industry best-practices, and work done by other teams.
· Partner with, coordinate, and influence multiple teams outside of EU Customer Fulfillment (Customer Service, Transportation, Amazon Logistics.), to support key initiatives.
· Be the voice of the customer (end customer and data consumer), aligning stakeholders with scalable mechanisms to incorporate our models into product and engineering decision-making processes.
· Drive and promote experimentation culture (e.g. A/B testing) with data-driven mindset and measurable approach.
· Master’s degree with 5 years relevant experience in a highly quantitative field (Machine Learning, AI, Computer Science, Statistics, Mathematics, Operational Research, etc.).
· Hands-on industry experience in predictive modeling and analysis, as an ML engineer or data scientist role, applying various ML techniques, and understanding the key parameters that affect their performance.
· Experience with R, Weka, SAS, SPSS, Matlab or other statistical/machine learning software.
· Proficient with using scripting language such as Python and data manipulation/analysis libraries such as Scikit-learn and Pandas for analyzing and modeling data.
· Experienced in using multiple data science methodologies to solve complex business problems (e.g. statistical analysis, research science, machine learning and deep learning techniques, data modeling, regression modeling, financial analysis, demand modeling, etc.).
· Experienced in handling terabyte-sized data sets, diving into data to discover hidden patterns, using data visualization tools, using SQL and databases in a business environment.
· Functional knowledge of AWS platforms such as S3, Glue, Athena, Sagemaker, Lambda, EC2, Batch, Step Function.
· Ability to distill informal customer requirements into problem definitions, dealing with ambiguity and competing objectives.
· Proven ability to communicate verbally and in writing to technical peers and leadership teams with various levels of technical knowledge, educating them about our systems, as well as sharing insights and data-driven recommendations.
· A PhD degree in a highly quantitative field (Machine Learning, AI, Computer Science, Statistics, Mathematics, Operational Research, etc.).
· 7+ years’ experience in a ML or Data Scientist role with a large technology company.
· Extensive knowledge and practical experience in several of the following areas: machine learning, statistics, NLP, deep learning, recommendation systems, dialogue systems, information retrieval, XGBoost, LightGBM, ElasticNet.
· Skilled with Python, Java, C++, or other programming language, as well as SQL or similar scripting language.
· Advanced knowledge and expertise with Data modelling skills, Advanced SQL with Oracle, MySQL, Redshift and Columnar Databases.
· Demonstrated industry leadership in the fields of Database and/or Data Warehousing, Data Sciences and Big Data processing.
· Experience mentoring team junior members.