ADCI Hiring for Data Scientist Ii, Scot Aim at Bengaluru, Karnataka, India Full Time

Job Description

• Bachelor or Master’s degree in Statistics, Applied Mathematics, Operation Research, Economics or a related quantitative field
• 3+ years of hands-on experience in predictive modeling and machine learning
• Proficiency in model development, model validation and model implementation
• Proficiency working with Python/R
• Experience leading, mentoring, and growing teams of scientists

Job summary
Have you ever ordered a product on Amazon and when that box with the smile arrived, wondered how it got to you so fast? Wondered where it came from and how much it cost Amazon? If so, the Amazon Global Supply Chain Optimization Technology (SCOT) organization is for you. SCOT organization owns Amazon’s global inventory management systems: we decide what, when, where, and how much we should buy to meet Amazon’s business goals and to make our customers happy. We do this for millions of items, for hundreds of product lines worth billions of dollars of inventory world-wide. Our systems are built entirely in-house, and are on the cutting edge in automated large-scale business, inventory and supply chain planning and optimization systems. We foster new game-changing ideas, creating ever more intelligent and self-learning systems to maximize the efficiency of Amazon’s inventory investment and placement decisions. Watch this video to learn more about our organization, SCOT: http://bit.ly/amazon-scot

The Automated Inventory Management team within SCOT seeks an experienced and motivated Senior Data Scientist. In this role, you will research and develop anomaly detection models and solve real world problems using the latest machine learning techniques. You will research new modelling techniques that can discover and interpret causal effects in our supply chain systems at scale. You will work closely with senior business leaders, product managers and engineers to build innovative scientific solutions that impact millions of inventory decisions each day.

Responsibilities include:

• Build models that can detect supply chain anomalies/ defects and explain variance to the optimal state
• Research new ways to improve predictive and explanatory models
• Directly contribute to the design and development of automated prediction systems and ML infrastructure
• Collaborate with other researchers, software developers, and business leaders to define the scientific roadmap for this team

• Extensive knowledge and practical experience in several of the following areas: explainable machine learning, time-series forecasting, statistics, deep learning, causal inference.
• Experience processing, filtering, and presenting large quantities (Millions to Billions of rows) of data.
• Practical experience with big-data processing libraries, eg. Apache Spark, Apache Beam, Hive, Apache Pig, Hadoop or similar