Data Scientist (ML Engineer)
With our industry leading sales performance platform fueled by data science and predictive insights,
is helping enterprises accelerate their sales, optimize their sales performance and exceed their revenue goals. With a proven track record of building high growth and highly successful technology companies, our team is completely focused on solving complex sales challenges and ensuring customer success.
We’re looking for a data scientist with a passion for technology to help drive informed business decisions. You will enjoy working with top-notch people, cutting edge technology, and the ability to see your insights turned into real value for our customers. The ideal candidate will have a background in a quantitative or technical field and will have some experience in data-driven decision making. You are scrappy, focused on results, a self-starter, and have demonstrated success in using analytics to drive understanding, growth, and success. This position to join our core Data Science team is located in our Menlo Park, CA office.
This is what you’ll do...
Build internal tools and processes to operationalize Machine Learning best practices within our existing platform and to automate manually intensive Data Science tasks.
Develop backend functionality for new customer-facing product features that leverage our Data Science capabilities.
Enhance existing modeling framework to support continuous improvement of predictions and surfacing of new insights.
What we’re really looking for...
Minimum of a Bachelor’s degree in a field that provides a strong quantitative background : Computer Science, Mathematics, Statistics, Applied Mathematics, Operations Research, Engineering, Economics.
Hands-on coder with proficiency in Python and the scipy stack (numpy, pandas, sklearn, matplotlib, etc).
Experience with advanced data modeling, machine learning algorithms, and data science techniques, including the majority of the following topics: decision trees, ensemble methods, boosting, cross validation, model evaluation, feature extraction and selection, hyperparameter tuning, dimensionality reduction, forecasting, clustering, linear regression and GLM, and other similar topics.
Strong command of discrete and continuous probability theory.
A great communicator — must be able to explain technical concepts and analysis implications clearly to varied audiences and be able to translate business objectives into actionable analyses
Experience with iPython Notebooks, PostgresDB, MongoDB, ElasticSearch, Tableau a plus.
In case you were wondering…
If you’re looking for a company where you will be challenged, respected, valued and thats invested in your personal development and offers solid compensation packages, this is an opportunity for you.