As a Data Scientist or an AI researcher intern, you will help formulate approaches to solve problems using various algorithms and data sources. You will incorporate an understanding of product functionality and customer perspective to provide context for those problems. You will use data exploration techniques to discover new questions or opportunities within your problem area and propose applicability and limitations of the data. Successful Data Scientists will interpret the results of their analysis, validate their approach, and learn to monitor, analyze, and iterate to continuously improve.

You will develop real-world machine learning algorithms in the domains of computer vision, natural language processing, recommender systems, and more.

You will increase productivity of ongoing research projects and help to productize them, publish research papers in top-tier machine learning venues and issue patents.

You will engage with peer stakeholders to produce clear, compelling, actionable insights that influence product and service improvements that will impact millions of customers. As a Data Scientist, you will also engage in the peer review process and act on feedback while learning innovative methods, algorithms, and tools to increase the impact and applicability of your results.
Due to nature of the Intern Program we are currently prioritizing applications from students with final graduation date of summer 2022 and beyond

Relevant candidates will have at least 2-3  of the qualifications listed below:

Currently pursuing MSc or PhD in Computer Science, Mathematics, Statistics, Applied Sciences like Physics or other quant-focused fields.
Proficiency using one or more programming or scripting language to work with data such as: Python, C++, Perl, or C#.
Relevant publications in machine learning / vision / NLP / speech / data mining conferences (e.g., NeurIPS, ICML, ICAAPS, AAAI, ICLR, CVPR, ICCV, ECCV, ACL, EMNLP, NAACL RecSys, KDD, WSDM, ICDM)
Experience and or project course work performing data analysis and applying statistics working with tools such as: R, MATLAB, AMPL, or SAS.
Experience or course work applying ML to a type of data, including the application of ML algorithms on large scale data sets, and understanding of various ML algorithms and evaluations techniques.
Hands on experience in development of deep / machine learning algorithms in  PyTorch/ TensorFlow for computer vision / speech / natural language processing applications.
Hands on experience with big data processing.
Experience in building industrial machine / deep learning systems.
Passion to learn from your peers, manager, and other stakeholders in the Data Science and AI domain.
Ability to interact with peers and stakeholders to drive product and business impact.
Strong interpersonal and communications skills.

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