Senior Software Engineer II, Machine Learning

🕒 April 29

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Narvar

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2012

🛍️ eCommerce

☁️ SaaS

🛒 Retail

💰 $30M Series C on 2018-08

eCommerce • SaaS • Retail

Narvar is a company that specializes in creating intelligent post-purchase experiences for ecommerce businesses. Their platform provides a range of services to enhance customer engagement and retention, from setting clear delivery expectations and proactive multi-channel messaging to seamless returns and exchanges. Narvar's solutions are designed to build loyalty by personalizing the consumer journey and optimizing reverse logistics, ultimately converting and retaining customers while increasing revenue and reducing costs. The company boasts a powerful network and integrations with popular platforms like Shopify, Zendesk, and Salesforce, and supports over 2,000 retailers globally. Narvar's services cater to a variety of industries including apparel, electronics, and beauty, providing exceptional post-purchase experiences through actionable insights and data-driven interactions across their ecosystem.

📋 Description

• Design and deploy machine learning algorithms for use cases spanning e-commerce, consumer trends, markets, logistics, and new products • Work on real-world consumer data for natural language processing, image classification, time series analysis, outlier detection, user modeling, etc • Work with large unstructured data • Be at the intersection of mathematics, machine learning, business, and computer science and impact millions of users through your work • Multiply the effect of your data science and data team members by building frameworks, tools, and methodologies that the entire team use • Provide thought leadership to a team through high quality write-ups, reviews, and a strong vision grounded in practical experience and a wider industry view

🎯 Requirements

• Strong machine learning skills. • Fluency in Python, PyTorch, Tensorflow, Pandas, numpy, and machine learning packages • Data Engineering skills and large data experience. You should have dealt with large amounts of data (TB) in a production setting, built world class data pipelines using cutting edge tools (e.g. Spark). • 10+ years of hands-on experience shipping models to production, working on a variety of problem spaces (eg: user modeling, spam classification, prediction, clustering etc) • MS in Computer Science, Statistics, Math, Science (physical or social), Engineering or similar quantitative and computation field plus 5+ years of industry experience • Strong software engineering and coding skills with the ability to write production quality code • Strong understanding of probability & statistics, machine learning, and algorithms • Experience with SQL and NoSQL databases • Experience working with Linux, shell scripting • Previous startup experience strongly preferred.