The Data Scientist will lead the Beautycon Data team and will be responsible for establishing the standard methods and technologies around data collection, management, interpretation, and actionable recommendations. The Data Scientist will take disparate data sets and create actionable data solutions. This role will lead creation and enhancement of our capabilities around predictive analytics, machine learning, and other industry leading methodologies to deliver maximum value to the company. Candidates should have a solid understanding of theory and concepts, but with a bias towards action and a track record of hands-on application.

Key Responsibilities:

• Lead predictive analytics and machine learning efforts in the areas of customer retention, long term growth forecasting, optimal product mix selection, optimization of marketing efforts
• Run self-directed analysis and experiments to test hypotheses
• Build and improve Beautycon’s personalization algorithms to better match our customers to products and content
• Develop models to predict customer churn and to better understand the underlying drivers and recommend prevention methods
• Design segmentation strategies that increase Beautycon’s understanding of our rapidly growing customer base
• Perform sentiment analysis on product reviews and customer feedback using natural language processing
• Present findings to executive team and team leads in a clear and actionable way
• Generate detailed analytics & reporting to support executive decisions and workflows including gathering business requirements, project planning, implementing logical design and data modeling
• Perform statistical and other data analysis to inform decision making and drive continual improvements
• Work with cross-functional teams to provide advanced data analysis and reporting
• Provide strategic recommendations for enhancing data analysis capabilities
• Build and oversee the Data team

Qualifications:

• 3+ years of relevant experience in a data science role preferred, but all highly-motivated candidates with a relevant academic background will be considered
• Masters or PhD in Statistics, Computer Science or other applied quantitative field
• Expert Level Experience with R and/or Python(pandas/numpy/scipy)
• Expert Level Experience with practical probability and statistics.
• Experience analyzing large data sets
• Experience in ecommerce or subscription based businesses is a strong plus
• Passion for analyzing large data sets, pattern recognition, and seeking better ways of doing things
• Effective presentation and communications skills
• Excited to work in a fast-paced, rapidly growing business
• Hands-on experience applying most or all of the following: constrained optimization, predictive modeling, clustering, machine learning.
• Experience scaling algorithms to handle large datasets
• Expert knowledge of statistics with ability to explain statistical concepts to non-technical audiences
• Experience with Map/Reduce tools (e.g. Hadoop, Pig, Hive, Shark)
• Solid understanding of a wide range of open source data mining / machine learning software packages (e.g. Weka, scikit-learn, MyMediaLite, Scalding)
• Experience applying statistics and machine learning techniques to real-world data
• Fluency in a scripting language such as Python or Ruby, for fast prototyping
• Ability to write complex SQL queries in short order

Pluses:

• Experience modeling data and designing feature sets
• Proficiency in R, Matlab, or another mathematical language
• Experience with integer programming
• Experience with search technologies (e.g. Solr, ElasticSearch)
• Knowledge of distributed algorithms and how to analyze them
• Java and/or Scala know-how