Pocket Outdoor Media is looking for a full time Data Scientist eager to put their data science and problem solving skills towards building the personalized fitness platform of the future. You’ll join the energetic team in our Boulder office and develop machine learning-based algorithms and models powering our cutting-edge platform utilizing large, diverse fitness datasets. You’ll receive competitive pay, benefits package (including medical, dental, vision), 401k, commuter benefits, and equity.
What you’ll do
- Lead development of custom predictive and prescriptive algorithms interfacing with large data sets, based on principles from statistics, machine learning, and operations research
- Create integrated solutions using Python modules (including Pandas, Numpy, Scipy, SQLAlchemy, and Tensorflow), PostgreSQL, and other tools as needed
- Work closely with engineers to help evolve proof of concept systems into production at scale
- Work the product development team to define desired requirements and capabilities
- Perform research as needed to identify the latest techniques from technical literature and apply them to relevant product features
- Identify and promote the use of new technologies, toolkits, and frameworks, areas of inquiry, ways of working, methods and approaches in Computer Science, Artificial Intelligence, Software and Research Engineering
What you’ll bring
- A degree in Computer Science, Engineering, Applied Statistics, Operations Research, Computational Biology, or a related analytical field
- 3+ years experience of statistical programming experience, including development of applied algorithms in production
- Demonstrated ability to develop algorithms in Python 3.x using Python libraries like Tensorflow, Keras, pandas, and numpy
- Detailed knowledge of computer science including data structures, data modeling, distributed systems, and software design methods
- Strong understanding of statistical inference, regression and classification, and the ability to explain rationale underlying data science-related decisions to a broader audience
- Knowledge of current best-practices, tools, and technologies for implementing machine learning pipelines
If possible, include references algorithms you’ve developed and/or research that you have published demonstrating your Data Scientist prowess. Be prepared to describe at least one data science project (thought process, planning, technical implementation) during your interview.