Senior Data Scientist

5+ years’ industry experience in Data Science.
M.S or PhD in Data Science/Machine Learning or closely related areas such as Computer Science, Operations Research, Applied Statistics, and Biomedical Informatics.
Deep grounding in machine learning techniques including regression methods, classification, Neural Networks, Deep Learning, as well as knowledge of clustering and unsupervised learning, time series forecasting and optimization methods.
Rigorous academic or experiential knowledge of the mathematical essentials for Data Science.
Technical experience in building intelligent data products, prediction models and recommendation engines using ML/AI.
Solid foundation with development of data analytics systems, including data exploration/crawling, feature engineering, model building, performance evaluation, and deployment of models.
Proficient with programming in Python and using Linux.
Hands-on experience handling large and distributed datasets.
Strong database skills and experience, including experience with SQL programming.
Experience with AWS or other cloud-based tools and technologies for data pipelining, model development, and deployment.

Develop statistical and machine learning algorithms to meet complex product requirements.
Work closely with stakeholders from Product Management, Engineering, and other business stakeholders to create impactful, intelligent features and products.
Collaborate closely with other team members including other Data Scientists, Machine Learning Engineers, and Data Engineers and ‘own’ the end to end process.
Mentor and train more junior team members and serve as a go-to expert in your area of statistics and machine learning.
Thoroughly and diligently document the model design, experiments, tests, validations, and live metrics and outcomes. You may be asked to write documents for use in the preparation of intellectual property and technical publications.

No preferred qualifications provided.