Senior Data Scientist II

Job Summary: 

The Senior Data Scientist will be leading in tackling challenging problems and creating statistical, machine learning, and deep learning models that impact millions of users. The Senior Data Scientist 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. This role will mentor junior team members to develop a strong future for Data Science at iHerb.

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.

• Mentor junior scientists, unlocking their potential and helping them grow in their careers

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 5 (five) years of relevant experience in data analysis or a related field (Data Scientist, Machine Learning Engineer, Statistician, or related field) and 2 (two) years 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.

Judgment/Reasoning Ability:  Able to identify, troubleshoot and resolve problems quickly using sound judgment, poise and diplomacy.  Ability to use judgment and reasoning skills and determine when to escalate issues, as required, in a timely manner.

Physical Demands:  The physical demands described here are representative of those that must be met by a Team Member to successfully perform the essential functions of this job.  While performing the duties of this job, the Team Member is regularly required to talk and hear. The Team Member is frequently required to sit, walk, climb stairs, use hands and fingers, bend, stoop and reach with hands and arms.  Reaching above shoulder height, below the waist, or lifting as required to file documents or store materials throughout the work day.  The Team Member may occasionally lift or move office products and supplies up to 25 pounds.  Proper lifting techniques are required.  Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.

Work Environment:  The noise in the work environment is usually moderate.  Other factors are:

• Hectic, fast-paced, with multi-level distractions

• Professional yet casual work environment

• Office environment

• Ability to work extended hours as required

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