Principal Data Scientist
3 weeks ago
We are seeking a skilled Principal Data Scientist to join our team at the Amazon Development Centre (India) Private Limited - A66. As a key member of our team, you will be responsible for building production-grade machine learning models to serve best-in-class shopping and delivery experience to millions of customers on Amazon.
The ideal candidate is an experienced data scientist or machine learning engineer who has built machine learning systems in production that delivers business impact at scale in a B2C industry. You are a self-starter who enjoys ambiguity in a fast-paced and ever-changing environment. You are extremely proficient in Python, SQL and distributed computing frameworks. You have excellent understanding of how machine learning models work under the hood. In addition, you may have worked with AWS infrastructure and causal uplift modeling techniques.
About the Team
We work closely with Product, Finance and Engineering to formulate business problems into scientific ones. We build large-scale data pipelines for training and evaluating the models using PySpark/SparkSQL, extensively clean and explore the datasets, train and evaluate ML models in a robust manner, design and conduct live experiments to validate model performance, and automate model inference and monitoring and on AWS infrastructure.
What You Will Do
- Work with Product, Finance and Engineering to formulate business problems into scientific ones
- Build large-scale data pipelines for training and evaluating the models using PySpark/SparkSQL
- Extensively clean and explore the datasets
- Train and evaluate ML models in a robust manner
- Design and conduct live experiments to validate model performance
- Automate model inference and monitoring and on AWS infrastructure
Basic Qualifications
- PhD, or Master's degree and 5+ years of applied research experience
Preferred Qualifications
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
- Strong understanding of statistical analysis (hypothesis testing and experiment design) and machine learning techniques for tabular data
- Experience in developing and implementing machine learning models for tabular data in production
- Publications in top-tier machine learning conferences
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