Senior Data Scientist

The Senior Data Scientist is accountable for understanding business problems to solve, performing data analysis, and providing quantitative solutions. This includes understanding and capturing business needs and requirements, formulating and prototyping prediction and optimization models, directing and verifying the implementation of mathematical procedures, communicating the results efficiently to both technical and non-technical audience, maintaining and improving backend models of existing products, supporting both internal and external customers with business and/or technical questions, and coaching data scientists. The Senior Data Scientist is expected to maintain a high level of professionalism, communicate clearly, and demonstrate a customer-focused attitude and approach to problem solving.

Job Responsibilities:

Development

• Work with customers (existing and potential) to understand business processes, problems and needs.
• Work with the business team to capture business requirements and recommend solutions.
• Collect and organize data from diverse sources.
• Perform extensive data analysis to identify and estimate statistical patterns.
• Formulate and prototype segmentation/clustering, prediction and optimization models.
• Communicate the findings, models and results to the science team, business team and/or customers.
• Explain mathematical designs to the product team and QA team.
• Help the QA team to verify the results of new mathematical codes.
• Improve the existing mathematical procedures.

Research

• Learn new mathematical methodology and algorithms by studying technical articles, books, papers and blogs.
• Research and propose innovative mathematical models.
• Publish technical articles and blogs.
• Mentor Data Scientists about the research procedure and data analysis.

Support

• Maintain the mathematical procedures of existing systems.
• Provide support for the implementation team to setup new mathematical components.
• Provide support for the support team to answer the 3rd level pricing questions.
• Provide support for the sales team to explain the existing systems.

Job Requirements:

• A MS degree is required in one of the following quantitative disciplines: Statistics, Operations Research, Applied Mathematics or related fields. A PhD degree is a plus.
• Minimum of 5 years hands-on experience in performing data analysis including manipulating large and diverse data, cleaning data, and estimating statistical models.
• Strong knowledge of data mining and machine learning techniques such as decision tree (CHAID/CART), clustering, segmentation, association rules, etc.
• Familiar with statistical models such as generalized linear regression, discrete choice model, etc.
• Must be able to build forecasting models with time series methods (e.g., exponential smoothing and ARIMA, etc.).
• Familiar with unconstrained and constrained optimization modeling using CPLEX, etc.
• Must be able to independently research academic and practitioner literatures in order to apply the most suitable technique to the problems.
• Hands-on experience using three or more languages like SQL/EXCEL, S-plus/R, SPSS/SAS, Python, C++/C#, etc.
• Experience in modeling and implementing Pricing and Revenue Management systems is highly desirable.
• Excellent communication skills, both written and verbal.
• Coach and lead data scientists in designated projects.
• Proven ability to work well in a team environment and under pressure.

EEO Statement