Although we expect you to have experience using a variety of modeling and algorithmic methods and familiarity with product analytics, marketing analytics, web analytics, business analytics, and customer lifetime value, we also expect you to apply strong business acumen to the models you build. You possess excellent communication skills and are able to engage with senior leaders to design well-constructed analyses and work cross-functionally with product managers and engineers to integrate your results into our operations.
You will not find big egos here. You will find a strong team of analysts that thrives equally on learning and teaching -- we value learning from the most junior to the most senior members of our team. We are passionate about our work, and our appetite for improving existing skills while acquiring new ones is insatiable. We practice and demand transparency – we work hard to spread, not hoard, our knowledge within our team and across the organization. We refer to ourselves as Data Scientists because, ultimately, our job is to acquire knowledge about the business so we can apply scientific techniques to drive profitable growth. If you share our values, we would love to hear from you.
- Learn and stay current with the latest techniques in statistical and machine learning and apply them to our analytical challenges.
- Learn our data model and the underlying physics that it represents.
- Identify and analyze customer behaviors for use in tactical and strategic decision-making and integration into our processes, operations, and products.
- Develop predictive models, classifiers, and other data products that will be used for personalization in a variety of contexts.
- Work with Engineering and Product teams to ensure the appropriate metrics and dimensions are incorporated into our data sets and to integrate our data products into our infrastructure to enable various types of personalization.
- BS, Masters, or PhD degree in a quantitative discipline (Economics, Finance, Statistics, Chemistry, Physics, Biology, Mathematics, Engineering, Computer Science, or MBA with emphasis in analytics).
- 12+ years' work experience in a data science role, including data mining, data transformation, pattern recognition, building statistical models, and delivering actionable insights
- Proficient at creating and analyzing large multi-dimensional data sets using open-source, parallel-processing frameworks, such as Apache Spark.
- Proficient with common programming languages such as Python, R, Scala and SQL.
- Expert on Machine Learning supervised and unsupervised methods: regression and classification techniques (Random Forest, SVM, Gradient Boosting algorithms, Apriori, K-Means clustering), stochastic methods, Natural Language Processing, etc.
- Ability to build, test, deploy and iterate statistical models and report on model performance/ROI.
- Experience with advanced machine learning techniques, such as deep learning systems, is a plus.
- Experience with customer analytics concepts, such as CLV modeling, churn modeling, real-time customer evaluation, recommendation engine is a plus.
- Experience with Microsoft Azure HDInsight technology stack is a plus.
- Experience with web analytics methods and frameworks – Omniture/Google Analytics
- Translating data into an informed story via visualization tools such as Qlikview or Tableau
- Excellent communication skills with strong ability to synthesize key insights into actionable solutions