Job Summary:
As a Data Scientist you will be tackling challenging problems and creating statistical, machine learning, and deep learning models that make an impact on millions of users. You will join a team of data scientists, machine learning engineers, and software developers who work closely with business partners to provide machine intelligence driven solutions and products to simplify and enhance the customer experience and to automate core business processes.
Job Expectations:
Create machine learning, deep learning, and statistical models that turn insights into robust products for our customers and business partners
Translate ambiguous business problems into analytical problems, bringing your stakeholders along the way
End-to-end analysis including data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations
Prototype and build analytical pipelines using various data sources to provide insights at scale.
Interact cross-functionally with a wide variety of teams and work closely with them to identify opportunities to improve on iHerb’s platform
Develop analytical solutions, forecasting, and optimization methods to improve the quality of iHerb’s user experience. Areas include product recommendation, end-user behavioral modeling, user engagement, pricing, fraud detection, etc.
Make business recommendations (e.g. cost-benefit, forecasting, experiment analysis) based on rigorous analysis
Knowledge, Skills and Abilities:
Experience with one or more programming or scripting languages (Python, R, C#, Java, or Scala)
Hands-on experience with statistical modeling and machine learning packages (scikit-learn, LightGBM, XGBoost, Keras, Pytorch, Tensorflow, statsmodels, Stan, etc.)
Deep understanding of at least one of the following: Operations Research, Statistical Modelling, Hypothesis Testing, Statistical Simulation, Probabilistic Modelling, or Time Series Analysis
Ability to gather data from multiple sources (SQL, Spark, etc.) and use data visualization packages to analyze the gathered data (Seaborn, Matplotlib, ggplot, Plotly, etc.)
Equipment Knowledge:
Experience with Microsoft Office Suite (Word, Excel, PowerPoint)
Experience with Google Business Suite (Gmail, Drive, Docs, Sheets, Forms) preferred
Experience Requirements:
Generally requires 3 (three) years relevant experience in data analysis or a related field (Data Scientist, Machine Learning Engineer, Statistician, or related field) and 1 (one) year of relevant work experience in data analysis or related field. (e.g., as a Data Scientist, Statistician, or related position).
Education Requirements:
Master's Degree in Computer Science, Statistics, Applied Mathematics, Physical Sciences, or related quantitative fields. Ph.D. highly preferred.