We are seeking a data scientist to participate as a key team member in envisioning, designing, coding, testing and improving algorithms that are central to our mission. This is an excellent opportunity for any experienced data scientist that has a track record of success within high performing, dynamic teams and that enjoys a start-up environment. Our leadership team has decades of combined experience leading, acquiring and selling successful Adtech and Analytics companies in public and private markets. If you want a challenging job that allows you to be creative, strategic and entrepreneurial while having fun working with a team of high performing individuals then we want to talk with you.
We are committed to building careers, not jobs. That means that developers can learn the capital funding process, and data scientists can learn B2B marketing. We want to help develop well-rounded business leaders – some of whom will use these skills within a technical domain, and others of whom will become company founders and general managers.
Beyond competitive cash compensation, we believe in equity participation as we're looking for dedicated folks willing to put in the effort to build a winning product and team.
KEY CHALLENGES WILL INCLUDE
• Identifying external data sets and developing API’s or other methods for accessing the information
• Fluidly self-educating on existing methods for modeling end-user behavior in a variety of contexts and/or developing new methods for doing this when necessary
• Designing experiments to answer targeting questions that improve application results
• Teaming with developers to embed algorithms in applications
• Understanding business economics, user motivations and other contextual information in order to guide analytical trade-offs, to determine minimum viable algorithm followed by intensive, iterative improvement.
THE SUCCESSFUL CANDIDATE
A successful candidate will be comfortable in a fluid, entrepreneurial environment, but one that is focused on developing reusable software application, not bespoke analytical solutions. He or she will likely have the following characteristics:
• 2+ years professional experience using statistical software (R, S-Plus, SAS or similar), relational and NoSQL databases and scripting languages (such as Python). Ideally R and Python.
• Familiar with general-purpose machine learning methods, such as neural networks, Bayesian networks, regression, decision trees, etc. Capable of self-teaching new algorithmic methods easily
• Well rounded top performer who is able to “crunch the numbers” one minute, and critically think through strategic issues the next.
• Self-starter with high degree of rigor, organization and discipline to get things done
• Can work with others in a team setting to find answers to challenging questions while exhibiting the ability to have fun – hopefully concurrently.
• Able to communicate as effectively in delivering complex data-driven findings with business people, as in discussing machine-learning specifications with an engineer.
• Strong math, physics, CS or similar degree from a leading program.