Head, Engineering - Data Sciences
BloomReach is a Silicon Valley firm that brings businesses the first open and intelligent Digital Experience Platform (DXP). BloomReach drives customer experience to accelerate the path to conversion, increase revenue, and generate customer loyalty.
With applications for content management, site search, page management, SEO optimization and role-based analytics, BloomReach is a central location for all players who manage customer experience to come together and intelligently drive business outcomes. BloomReach’s Web Relevance Engine (WRE) algorithmically understands content and users, matching demand and intent data from across the web. BloomReach is a Leader in the Gartner Magic Quadrant for WCM, with tools to unlock the powerful creativity of humans to improve omnichannel customer experiences at scale. Together, human and machine generate millions of dollars of proven incremental sales.
BloomReach's portfolio of customers include: Neiman Marcus, Staples, Mailchimp, and Air Miles. Created in 2009, BloomReach is headquartered in Mountain View, CA with offices worldwide and is backed by investment firms Bain Capital Ventures, Battery Ventures, NEA, Salesforce Ventures, and Lightspeed Ventures. Learn more: www.bloomreach.com
BloomReach Personalization is solving one of the digital world’s most fundamental problems: Helping people instantly find what they need when they need to find it. Our personalization platform relies on unique algorithms paired with machine learning and data science to create peerless commerce on the world’s leading retail sites.
Data Sciences Team is brain behind BloomReach Personalization. The team is responsible for the data science modules that power all the products of the company, including Analytics, Search Relevance, Personalization, Recommendation, Web Relevance Engine, and Content Intelligence. This team invents and applies machine learning, data mining, and informational retrieval algorithms to understand, identify, and improve web content discovery.
The enormous amounts of data generated by users is an advantage as well as a challenge at Bloomreach. We process data from 100s of customers, generating about 500 million customer interactions per day that drive billions of dollars of revenue. We have built industry leading algorithms in search/recommendations for commerce space that serve the most relevant experiences using Artificial Intelligence. We don’t settle on our laurels and we want to make further improvements while also taking on the challenge of building AI driven experiences beyond commerce.
We are looking for a hands on Engineering Leader to spearhead the Data Science and Machine learning charter. This person would be leading the design and implementation of core algorithmic components for search , recommendation and user understanding that are used to personalize the digital experiences for our customers.
Translate business requirements to machine learning solutions
Lead development and implementation of scalable algorithmic solutions for search, recommendation and user understanding
Set clear KPIs that measure the efficacy of various algorithms
Ensure advanced agile standards are maintained in research, development, QA, and implementation phases
Ensure excellence in delivery to internal and external customers
Build deep partnerships with business, product management, and technology leaders
Lead, hire, manage and mentor a global team of engineers
Contribute to BloomReach`s Intellectual Property through patents and/or external publications.
Required Skills & Experience :
- Masters Degree in Computer Science, Applied Mathematics, Linguistics or related discipline (PhD preferred).
10+ Years of strong working knowledge of Machine-learning algorithm development with Python, Java, and/or Scala
4+ Years of experience in scaling and managing teams. Managing distributed teams is a plus
Proven track record of building products/features using Natural Language Processing, Query Understanding and Semantic Search techniques
Experience with Big Data and search technologies – Spark/Hadoop/Kafka and SOLR