Staff Data Scientist

• We're looking for a Staff Data Scientist to join our Machine Learning team.
• You'll work closely with a team of engineers to create a platform on top of that data that will be leveraged by virtually every other product and system we have built or will build in the future.
• You'll be responsible for experimenting to create new models to improve Bazaarvoice products and retraining existing models.

Primary Duties of the Role:

• Apply (and extend) state-of-the-art natural language processing, machine learning, and statistical techniques to develop predictive models and optimization algorithms.
• Use sophisticated analytical methods to automate existing processes and enable new capabilities.
• Utilize machine learning and large-scale data mining techniques to discover and identify actionable patterns in the data.
• Mentor more junior Data Scientists and Data Analysts.
• Deep dive into the data to understand and apply patterns, while maintaining a sense of the big picture.
• Work closely with engineers & product managers to put research results into action.

Skills and Experience Necessary for the Role:

• Ability to independently create plans for projects and a track record of overseeing large / complex analytical projects spanning multiple teams.
• Hands-on experience with machine learning techniques, such as logistic regression, naïve bayes, SVM, decision trees, neural networks, and random forests.
• Practical experience applying statistical analysis (in A|B testing, causal inference, ML, etc.).
• A track record of delivering ML-enabled products from idea to delivering value in production.
• Experience researching, evaluating, and applying state-of-the-art Machine Learning techniques.

Requirements:

• Bachelor's Degree in Statistics, Computer Science, Mathematics, or equivalent work experience.
• 10+ Years of total experience.
• 5+ Years of Experience in Data Science or Data Analytics.
• 5+ Years experience analyzing data using SQL.
• 4+ Years experience with Python/Scala.
• 3+ Years Experience developing products on Public cloud Hosting platforms (ex. AWS, GCP, etc).