** THIS POSITION IS OPEN FOR CANDIDATES LOCATED IN USA OR ISRAEL **

Aterian (NASDAQ: ATER) is a rapidly growing e-commerce company founded on the premise that companies of the future will be offering consumer products based on data, artificial intelligence and machine learning.

We are reinventing how to rapidly and successfully identify new product opportunities by leveraging our proprietary platform, AIMEE. 

As a Lead Scientist you will be leading data scientists across our product ecosystem in delivering productionized, cutting edge data-science, ML and AI components. 

Our platform AIMEE analyzes millions of data points every day to produce insights for our business. We rely on a heavily distributed architecture and we work in the rapidly changing space of eCommerce, stretching the limitations of technology on a daily-basis. We’re a global group with talented teams working in New York, Seattle, Krakow, Lviv, Montreal and Tel Aviv. 

Responsibilities:

• Oversee machine learning, AI and algorithmic development for an e-commerce engine that automates product identification, financial analysis, feature product feature analysis, inventory management, marketing ad spend, pricing and sales.
• Lead a team of data scientists across teams, define and execute on the company’s AI/ML strategy

• Work with brand managers, and external stakeholders to create and enhance algorithmic e-commerce strategies

• Design and implement algorithms to tackle a wide variety of datasets using open source libraries, third party API’s and in house developed algorithms

• Design the machine learning process to work in the context of a highly scalable cloud based distributed microservice architecture

Preferred Qualifications

• At least 7 years of proven experience as a Data Scientist, similar role or career progression.
• Experience working as a data scientist in CPG/Retail/e-Commerce companies
• Deep knowledge in statistics, Machine Learning and Time Series Forecasting/Analysis
• Knowledge of data management, data engineering and visualization techniques 
• Experience in writing complex SQL queries and working in a multi-database environment
• Relevant scientific academic background - ability to read and implement insights from academic papers
• Knowledge in building production-ready code (Object Oriented, Design Patterns etc.) - a plus
• Experience with Big Data technologies such as Spark, Hadoop, Hive - a plus
• Experience in building NLP models incl. relationship extraction, entity extraction, topic modelling etc. - a plus
• Excellent communication skills in English

About the team

We’re a distributed team of engineers working across Poland/Israel/US developing a suite of products that are both analytical and transactional in nature. Our stack includes K8s, ElasticSearch, PostgreSQL, Spark,Redis, Cassandra, Citus and Kafka. We use data science, NLP and machine learning to solve problems in logistics (Fulfillment & Inventory optimization), Pricing optimization, marketing automation, demand forecasting, market intelligence, and robotic process automation.