Operations Research Intern

Job description

DESCRIPTION

About us:

Amazon is a company of builders. A philosophy of ownership carries through everything we do — from the proprietary technologies we create to the new businesses we launch and grow. You’ll find it in every team across our company; from providing Earth’s 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; it’s a place where motivated employees thrive, and ownership and accountability lead to meaningful results. It’s 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, we're 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 solve real world problems, if you have a passion for using machine learning/mathematical optimization 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 you’re motivated by results and driven enough to achieve them, Amazon is a great place to be. Because it’s 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, we’re 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, Transportation, HR, Employee Relations 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 /data mining/ operations research 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.) across multiple geographies.
· Closely collaborate with operations research scientists, data scientists, business analysts, BI teams, developers, economists and more on various models’ (including predictive/prescriptive 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

PREFERRED QUALIFICATIONS

Preferred Qualifications

· 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 it’s an experience in a similar field, even better!

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decision based on your experience and skills. . We believe passionately that employing a diverse workforce is central to our success. We make recruiting decision based on your experience and skills. We value your passion to discover, invent, simplify and build. We welcome applications from all members of society irrespective of age, sex, disability, sexual orientation, race, religion or belief.
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Desired profile

BASIC QUALIFICATIONS

Basic Qualifications

We want to hire the world’s 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, Machine Learning, 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, XPRESS/Gurobi/CPLEX).
· Some knowledge in writing scripts (Perl, Ruby) to manipulate data and developing software applications in traditional programming languages (C++, Java, Python).
· Knowledge of either linear programming, combinatorial optimization, integer programming, dynamic programming, network flows and algorithms or 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 pick up 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 have strong 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!