Paper is looking for a Data Scientist to join the growing R&D and analytics team. The Data Scientist will be responsible for performing research in natural language processing, machine learning, information retrieval, time series forecasting and optimization. The data scientist will be responsible for brainstorming and implementing algorithms to solve technical problems and is expected to adopt a scientific approach when conducting R&D experiments. They will spend a significant amount of time planning, documenting and evaluating the results of their experiments, working closely with our research scientist. They must be self-directed and comfortable conducting applied research in collaboration with a wide range of stakeholders and functional teams. The ideal candidate will have a strong background in mathematics/statistics/computer science or a related field.

Responsibilities

• Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
• Mine and analyze data from the company databases to drive optimization and improvement of product development and business strategies.
• Assess the effectiveness and accuracy of new data sources and data collection techniques.
• Develop custom data models and algorithms.
• Use predictive modeling to improve service delivery, customer experience, and other business outcomes.
• Develop company A/B testing framework and test model quality.
• Coordinate with different functional teams to implement models and monitor outcomes.
• Develop processes and tools to monitor and analyze model performance and data accuracy.

Requirements

• 5-7 years of experience manipulating data sets and building statistical models, with a Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field.
• Strong problem solving skills with an emphasis on product development.
• Experience using statistical computer languages (Python, R, Matlab, SLQ, etc.) to manipulate data and draw insights from large data sets.
• Experience working with and creating data architectures.
• Experience visualizing/presenting data for business stakeholders
• Knowledge of a variety of machine learning techniques (supervised and unsupervised, clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Experience creating and applying advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
• Excellent written and verbal communication skills for coordinating across teams.
• A drive to learn and master new technologies and techniques.
• Experience using cloud services is a plus
• Experience analyzing data from 3rd party providers, e.g. Google Analytics, is a plus
• Experience using graph learning is a plus
• Experience putting Machine Learning models into production is a plus

Position can be located in any geography in the US or Canada.

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