DocuSign

San Francisco
1,001-5,000 employees
Since its inception in 2003, DocuSign has been on a mission to accelerate business and simplify life for companies and people around the world.

Data Science Intern - Manage & Analyze

Data Science Intern - Manage & Analyze

This job is no longer open

Data Science Intern - Manage and Analyze
Engineering & Tech Ops | San Francisco, California (Remote) 

Our agreement with employees

DocuSign is committed to building trust and making the world more agree-able for our employees, customers and the communities in which we live and work. You can count on us to listen, be honest, and try our best to do what’s right, every day. At DocuSign, everything is equal. We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relationships, and to do the work of their life. Best of all, you will be able to feel deep pride in the work you do, because your contribution helps us make the world better than we found it. And for that, you’ll be loved by us, our customers, and the world in which we live.

The team

The Agreement Intelligence team builds Machine Learning solutions that power insights and automation for the entire DocuSign Agreement Cloud. We have built industry-leading Computer Vision and Natural Language Processing products and features, all leveraging an enormous wealth of text and image data. Our group is pioneering the Smart Agreement Cloud of the future and we’re looking for experienced, driven, and diverse industry experts who want to be part of building that future together. No matter who our customer is, where they do business, or what they’re agreeing on, our team would like to simplify and optimize their business processes around contract negotiation, execution, and post-signature analysis. Our ultimate goal is to make the world more agreeable by empowering all of our customers with automated legal expertise.

This position

DocuSign is looking for a passionate, talented, and inventive data scientist interns to help build industry-leading state of the art natural language processing solutions. You will be leveraging data mining, deep learning, content understanding, document processing and more. You will prototype machine learning models that deliver more personalized and automated customer experiences throughout the DocuSign Agreement Cloud.

This position is an Individual Contributor role and reports to a Director of Engineering.

Responsibilities

• Building predictive solutions with established tools and packages
• Working within the ML team to perform research, testing and evaluation of existing and emerging NLP/NLU methods and technologies that could be effectively applied to contractual/legal data
• Working closely with Product Management to translate product requirements into robust, customer-agnostic machine learning architectures
• Working closely with Data Engineering and Model Deployment teams to take models from prototype to production-ready states

Basic Qualifications

• Bachelor’s degree in computer science, statistics, econometrics, operations research, applied mathematics or an equally computational field and enrolled during the term of the internship.
• This role is not eligible for candidates requiring CPT/OPT or sponsorship in the future

Preferred Qualifications

• Experience in designing, developing, deploying and monitoring machine learning and deep learning solutions, specifically in the context of natural language processing and natural language understanding
• Demonstrated experience developing and deploying sequence-based Deep Learning models
• Experience programming in PyTorch, TensorFlow, or spaCy
• Strong desire to stay ahead of industry trends & technologies with a commitment to continuous learning
• Demonstrated experience of performing experimental design with statistical rigor
• Experience with Machine Learning Concepts - Training, Validation, Testing, Precision/Recall, Bias/Variance etc.
• Experience in extracting, cleansing, and manipulating large, diverse structured and unstructured data sets.
• Knowledge and experience in applying ML algorithms and technologies to NLP tasks such as Named Entity Recognition, POS tagging, Parsing, Sentiment Analysis, Clustering, etc.
• Experienced Python programmer, especially in the context of established deep learning frameworks.

Engineering @ DocuSign

A problem that takes 5 minutes to solve is not interesting. A problem that takes 5 years to solve is fun. We like to think about complex, global challenges that cross cultures and legal jurisdictions and that impact millions of people and businesses. We hire people with a broad set of skills, and they are working on how to create never-been-done-before solutions that scale. We are creating revolutionary solutions that change the way people work, live and connect … and we see our work go live. We see its impact.

About us

DocuSign® helps organizations connect and automate how they prepare, sign, act on, and manage agreements. As part of the DocuSign Agreement Cloud, DocuSign offers eSignature: the world's #1 way to sign electronically on practically any device, from almost anywhere, at any time. Today, hundreds of thousands of customers and hundreds of millions of users in over 180 countries use DocuSign to accelerate the process of doing business and simplify people's lives. Plus, we save more trees together! And that’s a good thing.

DocuSign is an Equal Opportunity Employer[BA2] . DocuSign is committed to building a diverse team of talented individuals who bring different perspectives to the discussion and who feel a sense of inclusion and belonging when they join our team. Individuals seeking employment at DocuSign are considered without regards to race, ethnicity, color, age, sex, religion, national origin, ancestry, pregnancy, sexual orientation, gender identity, gender expression, genetic information, physical or mental disability, registered domestic partner status, caregiver status, marital status, veteran or military status, citizenship status, or any other legally protected category.

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