Lead Data Scientist at Paper

Paper is looking for a Lead Data Scientist to join the growing R&D and Data Science team. In this role, you will be responsible for managing technical aspects of data science projects to ensure the success of delivered solutions. You will spend a significant amount of time designing, planning and executing technical solutions. You will work closely with our applied research scientists and engineers across the organization. You must be self-directed and comfortable providing guidance on applied research projects in Analytics and Machine Learning domains. You are eager to collaborate 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.
This position can be located in any geography in the US or Canada.
Responsibilities:

Identify strategic technical objectives and lead data science technical roadmaps from ideation to implementation.
Improve the technical quality of the codebase via developing quality standards, leading training sessions, and enforcing code review processes.
Work with stakeholders throughout the organization to identify roadblocks and execute to unblock technical hurdles.
Mentor and coach data scientists on the team by providing direct feedback or comments in code reviews as well as leading pair sessions.
Lead rituals such as planning and retrospective meetings and backlog grooming to ensure consistent velocity.
Manage the team’s workload by controlling technical debt.
Collaborate with different functional teams and communicate technical and non-technical decisions.

Qualifications:

5-7 years of experience in data analytics and building statistical models, with a Master’s or Ph.D. in Statistics, Mathematics, Computer Science or another quantitative field.
+2 years of experience leading highly technical and analytical teams. 
Proficiency in Python and Data science libraries including Numpy, SciPy, Pandas, Scikit-Learn, Tensorflow, Pytorch, MatplotLib and Seaborn (R and Matlab are a plus).
Experience manipulating data and drawing insights from large data sets.
Solid knowledge of production infrastructure and pipelines for Data science solutions.
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 working with and creating data architectures.
Knowledge of GCP cloud services.
Experience visualizing/presenting data for business stakeholders.
Strong problem-solving skills with an emphasis on product development.
A drive to learn and master new technologies and techniques.
Excellent written and verbal communication skills for coordinating across teams.

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.
24/7 access to Paper for family members K-12.   

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