Would you like to be a part of shipping groundbreaking technology of large scale systems with natural language processing and artificial intelligence? You will be working with multi-functional engineering, project management and quality teams to help identify product and process quality issues and improve Siri customer experience. Imagine being part of the team that crafts the intelligent assistant which helps millions of people get things done — just by asking.
As a Data Engineer, you will be able to work with large test data sets across the entire Siri Experience: Make recommendations to significantly improve the quality of every release. Define the key metrics that quantify the performance and behavior of different features across multiple platforms. Provide data driven insights to shape the product road maps. Predict and preempt production issues even before new features are shipped.
Siri Data Engineer drives product quality, test effectiveness and process efficiency by providing data driven insights supporting Siri Experience. As a part of this team, you are expected to organize data, and share unique, actionable and valuable business insights that can improve the product, process and policy within the organization. In particular, you will be defining performance metrics, evaluating test cases and devising regression conditions for different models to test the robustness of the models.
Your curiosity to understand how the product is used and ability to make customer experience delightful by providing data driven recommendations takes this team a long way.
Skills & requirements
Contributes to the analysis of ML model performance and the end-to-end testing platform
Implement solutions that reach production software
Strong knowledge of relational databases and large scale distributed systems such as Hadoop and Spark along with querying languages including SQL, Hive and SparkSQL
Experience in designing a data warehouse over a complex network of data sources that can cater to all transactional and analytical needs of data consumers (humans and technology)
Harness data to produce unique, valuable and actionable business insights
Experience with python, R, data science toolkits, such as pandas, dplyr, NumPy, etc
Applied statistics skills, such as hypothesis testing, experimental design, sample size determination and non-parametric statistics
Practical experience with and theoretical understanding of algorithms for classification, regression, clustering, and anomaly detection
Ability to come up with datasets that test the boundary conditions of the models
Desired experience with machine learning models and NLP.
Present ideas to stakeholders to drive improvements within the organization
Excellent presentation skills, distilling complex analysis and concepts into concise business-focused takeaways
Creativity to engineer novel features and signals, and to push beyond current tools and approaches
Ability to communicate the results in a clear and effective manner to leadership teams to influence the overall quality of the product.
Comfortable supporting, collaborating and communicating with senior management and able to build strong working relationships through active listening, delivering promised results, and establishing trust.
Ability to initiate and drive projects to completion with minimal guidance in a fast-paced dynamic environment.
High level of professionalism, energy and sense of urgency to “make things happen” and resolve issues.
Experience in rapid development cycles, fail fast thinking is highly desirable.
Great teammate with a positive attitude, strong sense of empathy with ability to make decisions.
B.S, M.S or Ph.D. in Computer Science, Statistics, Engineering or related fields
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