Data Scientist (Remote - US)
Raleigh, NC /
Engineering & Data Science – Data Science & Analytics /
About the Team
The Data Science Team is responsible for research and development of end to end solutions for search related analytical problems. We collaborate with consultants and customers to learn user needs, gather data, design and prototype solutions, as well as validate preliminary results. We continuously explore new AI technologies, and join industry best practices with the latest ideas from academia to turn them into useful products. We work closely with engineering to put our algorithms into production and out into the world.
Our research areas include a variety of topics like, semantic search, relevance tuning/assessment, recommender systems, knowledge graphs, NLU and A/B testing.
You understand common Machine Learning and Deep Learning algorithms, know when a certain algorithm is or is not the right tool for the job, and understand the impacts of different parameter settings.
You have strong experience with recommendation and relevance algorithms, NLP expertise with document classification/clustering techniques and summarization. You are able to code an algorithm from scratch based on paper or ideas, invent new or modify existing algorithms, and maybe have interetesting publications or patents.
Most importantly, you are able to work collaboratively with a diverse community of personalities spread across multiple time zones, leveraging your excellent communication skills to make sure everyone is on the same page
- 3+ years of professional R&D experience
- Strong CS skills, ability to write efficient and easy to understand code in Python
- Good knowledge of the common DS and NLP libraries such as pandas, numpy, scikit-learn, spacy, transformers
- Experience with the DL frameworks: PyTorch or Keras/Tensorflow
- A mathematics based degree, advanced preferred, or equivalent experience
- Publication record in NLP or IR fields
- Familiarity with Java
- Familiarity with microservices and cloud technologies like Docker and Kubernetes
- Familiarity with search engines such as Lucene/Solr or Elasticsearc
Bonus points for:
Please note that at this time Lucidworks is unable to sponsor US employment authorization (both new and transfer).
Lucidworks is leading digital transformation by fusing the power of search and artificial intelligence to create connected experiences for work, shopping, research and support.
Fusion is our cloud-native ML-powered search platform that integrates open-source projects Spark and Solr with our proprietary code for query intent prediction, low latency search, hyper-personalization and smart app creation. Our products include applications that run on the Fusion platform including Predictive Merchandiser, which helps ecommerce teams harness the power of ML to improve ecommerce conversion and Smart Answers, which enhances chatbots and virtual assistants with natural language processing and deep learning. We believe in building a team to deliver these products that make searching for insights a uniquely personal experience for a worldwide community of users.
Our roots are in Apache Solr, the global search standard used by 90 percent of U.S. Fortune 500 companies. Our team includes contributors and committers to Solr as well as some of the world's foremost machine learning innovators. We are trusted by the world's largest brands to deliver personalized digital experiences across many industries, including: insurance, banking, capital markets, manufacturing, media, oil & gas, retail, software, and telecommunications. Those customers include companies like: Aetna, Morgan Stanley, Reddit, Red Hat, Uber, Verizon, and Wells Fargo. We also serve government agencies in the civilian, defense and intelligence sectors, including the United States Federal Reserve and the U.S. Census Bureau.
Lucidworks believes in the power of diversity and inclusion to help us do our best work. We are an Equal Opportunity employer and welcome talent across a full range of backgrounds, orientation, origin, and identity in an inclusive and non-discriminatory way. Applicants receive consideration based on the relevant talents, skills, and experiences they offer to our company. Thank you for your interest and we look forward to learning more about you.