We want to hire the worlds brightest minds, and offer them an environment in which they can learn and help improve the experience for our customers.
- You are currently working towards a 2+ years university degree in Statistics, Econometrics, Applied Mathematics, Computer Science, Operations Research or a closely related field.
- Excellent written and verbal communication skills in English.
- You must have the right to work in the country you are applying for.
- You are able to use at least 2 statistical modeling/programming languages or toolboxes (R, SAS, SPSS, Matlab, Python Data Science Stack).
- Some knowledge in writing scripts (Perl, Ruby) to manipulate data and developing software applications in traditional programming languages (C++, Java, Python).
- Knowledge of supervised learning methods (linear and logistic regression, generalized linear models, decision trees, random forests, support vector machines, graphical models, neural networks, etc.) as well as unsupervised learning methods (K-means, hierarchical clustering, association rules, principal components, etc.)
- Very strong self-learning skills. Ability to pickup and adapt modeling methods from other disciplines or leverage methods from other skilled colleagues in other departments in solving problems.
- You are results-driven with analytical skills and the ability to innovate and simplify current processes and practices.
- You should havestrong decision making skills, that use sound reasoning and when required use consultation to achieve consensus.
- The personal drive and enthusiasm that makes you stand out from the crowd!
Job title: Data Science Internship
Amazon is a company ofbuilders. A philosophy of ownership carries through everything we do - from the proprietary technologies we create to the new businesses we launch and grow. Youll find it in every team across our company; from providing Earths biggest selection of products to developing ground-breaking software and devices that change entire industries, Amazon embraces invention and progressive thinking. Amazon is continually evolving; its a place where motivated employees thrive, and ownership and accountability lead to meaningful results. Its as simple as this: we pioneer.
With every order made and parcel delivered, customer demand at Amazon is growing. And to meet this demand, and keep our world-class service running smoothly, were growing our teams across Europe. Delivering hundreds of thousands of products to hundreds of countries worldwide, our Operations teams possess a wide range of skills and experience and this include software developers, data engineers, operations research scientists, and more.
About these internships:
Whatever your background, if you are excited about modeling huge amounts of data and creating state of the art algorithms to solvereal world problems, if you have a passion for using mathematical optimization, including linear programming, combinatorial optimization, integer programming, dynamic programming, network flows and algorithms to design optimal or near optimal solution methodologies to be used by in-house decision support tools and software, if you enjoy solving operational challenges by using computer simulations, and if youre motivated by results and driven enough to achieve them, Amazon is a great place to be. Because its only by coming up with new ideas and challenging the status quo that we can continue to be the most customer-centric company on Earth, were all about flexibility: we expect you to adapt to changes quickly and we encourage you to try new things.
Amazon is looking for ambitious and enthusiastic students to join our unique world as interns. An Amazon EU internship will provide you with an unforgettable experience in a fast-paced, dynamic and international environment; it will boost your resume and will provide a superb introduction to our activities.
As an intern in Ops Research and modelling, you could join one of the following teams: Supply Chain, Amazon Logistics, Transportation, Prime Now, Inventory Placement and more.
You will put your analytical and technical skills to the test and roll up your sleeves to complete a project that will contribute to improve the functionality and level of service that teams provides to our customers. This could include:
- Analyze and solve business problems at their root, stepping back to understand the broader context
- Apply advanced statistics and data mining techniques to analyze and make insights from big data (data sets could include: historical production data, volumes, transportation and logistics metrics, simulation/experiment results etc.) in order to forecast, across multiple geographies.
- Closely collaborate with operations research scientists, business analysts, BI teams, developers, economists and more on various models (including predictive models) development.
- Perform quantitative, economic, and/or numerical analysis of the performance of supply chain systems under uncertainty using statistical and optimization tools to find both exact and heuristic solution strategies for optimization problems.
- Create computer simulations to support operational decision-making. Identify areas with potential for improvement and work with internal teams to generate requirements that can realize these improvements.
- Create software prototypes to verify and validate the devised solutions methodologies; integrate the prototypes into production systems using standard software development tools and methodologies.
- Convert statistical output into detailed documents which influence business actions
- Experience with large-scale data processing platforms such as Apache Spark and Hadoop.
- Knowledge Scala/ Spark or PySpark.
- Experience in data mining, SQL, ETL, etc. and using databases in a business environment with large-scale, complex datasets.
- Knowledge of business intelligence reporting tools (OBIEE, Business Objects, Cognos, Tableau, MicroStrategy).
- Familiarity with supply chain management concepts - forecasting, planning, optimization, and logistics - gained through work experience or graduate level education
- Ability to work successfully in an ambiguous environment, to meet tight deadlines and prioritize workload even when faced with conflicting priorities.
- Previous work experience - a summer job, internship or full-time role; if its an experience in a similar field, even better!