Bankrate is a technology company committed to producing the most reliable, personalized and highest quality content and data to serve the financial needs of consumers. We rely on a talented team of expert technologists who help Bankrate learn from a wide variety of data, both internal and external, as well as structured, semi structured and unstructured sources of data. Bankrate seeks a Data Scientist to join the Data Science Group applying machine learning and many other statistical methods to meet this challenge.

Responsibilities

• Reframe consumer and business objectives as machine learning tasks.
• deliver actionable insights, accurate predictions, and effective optimization.
• Implement and execute machine learning research with reliability and reproducibility.
• Communicate results and impact to business stakeholders.
• Collaborate with engineering teams to build data products and integrate into process throughout Bankrate.

Technical Qualifications:

• PhD with 1+ years, or MS with 4+ years experience in computer science, applied mathematics, or other quantitative computational discipline.
• Experience with open source machine learning and statistical analysis tools
• Coding experience, either in Python or R (knowledge of both is a plus).
• Ability to communicate complex ideas in data science to relevant stakeholders.
• Working knowledge of SQL and manipulating large structured or unstructured datasets for analysis in Python or R.
• Preferred: experience with Numpy, Pandas, Scikit Python libraries.
• Good knowledge in multivariate regression, random forests, classification algorithms & learning methods (supervised and unsupervised)
• Preferred: Working knowledge of MapReduce and related technologies.

Non-Technical

• Excellent analytical and problem-solving skills
• Strong oral and written communication skills
• A passion for empirical research and for answering hard questions with data.
• Proven record of solving challenging problems in academia and/or industry.
• Eagerness to collaborate with both technical and non-technical colleagues across various organizations.