Head of Data Science & Applied Machine Learning
Santa Clara Valley (Cupertino), California, United States
Software and Services
+ You have expert level knowledge of applied regression techniques including, but not limited to: Linear, Logistic, Mixed models, Distributed Lags, Time Series, General Linear Models & Simultaneous Equations. You will also have experience in the use of Neural Network models for sales forecasting and GAM models.
+ You are also an expert in application of Multivariate techniques like - Random Coefficient models, Canonical Discriminant models, Exploratory and Confirmatory Factor Analysis, Canonical Correlations.
+ Conceive and coach the design of end to end scripted analytics solutions using SAS, SQL/TeraData as well as modern analytical systems in Spark + Hadoop with Python or R.
+ Expertise in statistical data analysis and mathematical physics methodologies for unsupervised & supervised learning algorithms. Expertise in a wide variety of techniques including neural nets, deep neural nets, boosted trees, support vector machines. Algorithm development in graph mining and social network analysis also highly desired.
+ Demonstrated mastery of all aspects of the data pipeline including data storage systems (both relational and noSQL), modern ETL, aggregation/projection strategy, SDLC in a data engineering, and performance optimization
- You are a top-tier data scientist with 10+ years of experience in forming teams, organizing analytical processes and workflows, and mentoring junior team members - You are a hands-on leader who can develop high performing teams to meet the needs of a highly dynamic and complex business. - You have a passion for applied empirical analytics and answering hard questions with data, and the demonstrated ability to conceptualize, promote and implement business insights - You will have the ability to use advanced machine learning techniques for driving highly applied analyses and tools to directly drive revenue. - Have a strong passion for conceptualizing, documenting and deploying complex analytical plans to take on business problems. - Confirmed collaboration, communication and story telling skills with ability to adapt and connect across a variety of audiences. This includes strong writing, and data visualization skills with the ability to communicate complex quantitative analysis in a clear, precise, and actionable manner to senior executives. - Partner with senior leaders across the three focus areas to understand business goals, consult on data strategies and produce repeatable outcomes - Handle econometric analytics projects through all phases, including data quality, data modeling, statistical analysis, data visualization and presentation of results and deliverables. - Leading ongoing and ad-hoc analyses and predictive analytics to provide leadership with actionable insights at tactical and strategic levels. - Partner with the data engineering and BI team to Run workflows, requirements and project roadmap with Apple's IT organization to ensure consistent data availability, data quality and data accessibility for your projects. - Be a self-starter, driven, accountable and a highly high-energy leader. - Background in payments and/or physical retailing/merchandising analytics experience highly preferred.
**Education & Experience**
Advanced degree in Applied Econometrics, Statistics, Data Mining, Machine Learning, Analytics, Mathematics, Operations Research, Industrial Engineering, or related field. Ph.D is highly preferred.
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