Paper is looking for an Intermediate Data Scientist - NLP to join the growing R&D team. You will be responsible for performing research and applying techniques in natural language processing, machine learning and information retrieval. 

In this role, you will be responsible for designing and implementing algorithms to solve technical problems and you are expected to adopt a scientific approach when conducting R&D experiments. you will spend a significant amount of time planning, building, and deploying NLP custom and off-the-shelf solutions while working closely with our engineers. You should be self-directed and comfortable conducting applied research in collaboration with a wide range of stakeholders and cross-functional teams. As an ideal candidate, you need to have a strong background in mathematics/statistics/computer science or a related field.

This position can be located in any geography in the US or Canada.

Responsibilities:

• Develop, evaluate and deploy ML / NLP techniques.
• Mine and analyze data from the company databases to create standardized datasets.
• Develop processes and tools to monitor and analyze model performance and data accuracy.
• Assess the effectiveness and accuracy of new data sources and data collection techniques.
• Use predictive modeling to improve service delivery, customer experience, and other business outcomes.
• Develop custom data models and algorithms.
• Coordinate with different functional teams to implement models and monitor outcomes.

Qualifications:

• +2 years of hands-on experience building neural networks, statistical models and machine learning techniques, with a Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field or +4 years of experience in ML development teams.
• Extensive experience with Python and common data science libraries (Numpy, Scipy, Pandas, Matplotlib, Seaborn).
• Thorough familiarity with machine learning libraries (Scikit-learn, TensorFlow, Pytorch) and NLP libraries (NLTK, spaCy, CoreNLP, Gensim, TextBlob).
• Knowledge of a variety of machine learning techniques (supervised and unsupervised, clustering, regression, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Experience with putting Machine Learning models into production.
• Experience with visualizing/presenting data for business stakeholders.
• Strong problem solving skills with an emphasis on product development.
• Excellent written and verbal communication skills.
• A drive to learn and master new technologies and techniques.
• Experience using graph learning is a plus.
• Knowledge of GCP cloud computing services is a plus.

Job perks:

• Work with a dynamic team that provides support whenever you get stuck.
• Remote first environment.
• Annual company-wide meetup.
• Opportunity for career development with a fast-growing company.
• A unique opportunity to make an impact by making education more equitable.
• Stipend to help support the growth of your home office.
• Unlimited access to tutoring for children of Paper employees.  

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