Primary Duties and Responsibilities:
Produce innovative solutions driven by exploratory data analysis from complex and high-dimensional datasets. Apply knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement. Use a flexible, analytical approach to design, develop, and evaluate predictive models and advanced algorithms that lead to optimal value extraction from the data. Generate and test hypotheses and analyze and interpret the results of product experiments.
- Translate business problems into data science problems, determine criteria for evaluating success
- Work with Big Data coming from numerous sources
- Extract, clean, transform and process very large amounts of structured and unstructured data to prepare for data science initiatives (data wrangling)
- Apply machine learning, time series and other data science techniques to forecast sales volumes, usage of products, membership benefits, etc.
- Build deployable machine learning models that can support solutions for cross sell, sentiment analysis, improved customer experience, etc.
- Research new machine learning solutions for complex business problems
- Create data visualizations to illustrate findings in BI tools such as Tableau
- Communicate findings to business partners and executives
- Mentor junior Data Scientists
- Master’s Degree in Computer Science, Statistics, or similar area of study preferred.
Works in a temperature-controlled office environment.
- A Bachelor’s degree in Computer Science, Statistics, or similar area of study; or in the alternative, a combination of education, certifications and work experience equivalent to a Bachelor's degree in Computer Science, Statistics, or similar area of study.
- 5+ years’ experience with statistical modeling tools such as R, and scripting languages such as Python or Scala
- 2+ years’ experience with applying machine learning techniques to real-world problems
- 2+ years machine learning experience with supervised and unsupervised learning algorithms
- 4+ years’ experience using statistical techniques including linear/logistic regression, decision trees and cluster analysis
- 4+ years’ experience with advanced SQL queries
- Experience working with unstructured data
Knowledge and Skills:
- Intermediate knowledge of big data technologies such as Spark
- Familiarity with BI Tools such as Tableau, MicroStrategy, Data Studio, etc.
- Experience with machine learning packages