Uncubed
   

Research Scientist - NLP

Kensho, New York City, NY

GLOBAL ANALYTICS TECHNOLOGY THAT BRINGS TRANSPARENCY TO COMPLEX SYSTEMS

Duration: Full-Time


Who We Are

Kensho is a 100-person AI and machine learning company, centered around providing cutting-edge solutions to meet the challenges of some of the largest and most successful businesses and institutions. Our toolkit illuminates insights by helping the world better understand, process, and leverage messy data. Specifically, our solutions largely involve natural language processing (NLP) and include speech recognition (ASR), entity linking (Named Entity Disambiguation), structured document extraction, automated database linking, text classification, and more. We are continuously expanding our portfolio and are looking for passionate researchers to help us build and deploy state-of-the-art models across a variety of domains!

At Kensho, we believe in flexibility-first, and give our employees the opportunity to work from where they feel most productive and engaged (must be in the United States). We also value in-person collaboration, so there may be times when travel to one of our Kensho hubs (NY/DC/MA) will be required for team meetings or company events.

About The Role

At Kensho, we hire talented people and give them the freedom, support, and resources needed to accomplish our shared goals. As we expand our R&D efforts, we are currently seeking a Research Scientist to join our NLP team.

You will actively conduct and publish research that concerns one or more of the following core NLP problems:

- Structured document extraction and representation
- Entity linking
- Coreference resolution
- Extreme multiclass text classification
- Question answering
- Financial NLP

What You’ll Do

  • Collaborate with senior product and engineering leaders to identify the most promising problems to pursue
  • Develop novel, state-of-the-art NLP models that can scale to billions of documents
  • Work closely with ML Engineers and fellow Research Scientists
  • Contribute to a stellar engineering culture that values excellent design, documentation, testing, and code
  • Share your research results with your colleagues (presentations) and the world (published papers, patents, and blog posts)

Who You Are

    Outstanding people come from all different backgrounds, and we’re always interested in meeting talented people! Therefore, we do not require any particular credential or experience. If our work seems exciting to you, and you feel that you could excel in this position, we’d love to hear from you.

    That said, most successful candidates will fit the following profile, which reflects both our technical needs and team culture:

  • Hold a PhD in Computer Science, Applied Math, or a similar field (or a M.S. with significant research experience)
  • Have published in a top-tier ML/NLP conference (e.g., ACL, NAACL, EMNLP, NeurIPS, ICML)
  • Are proficient in writing code in PyTorch, Tensorflow, or JAX
  • Have experience with the techniques required to work effectively with large, messy real-world data
  • Prefer to collaborate iteratively on hard problems with your teammates rather than spending stretches of time working alone and presenting your results intermittently
  • Have a love for learning new skills and domains, and are excited to share your knowledge freely, proactively, and effectively with others who are interested
  • Are a generous and fun teammate and can take your work seriously without taking yourself too seriously

Technologies We Love

  • ML: PyTorch, NetworkX, Weights & Biases
  • Deployment: Airflow, Docker, EC2, Kubernetes, AWS
  • Datastores: Postgres, Elasticsearch, S3
At Kensho, we pride ourselves on providing top-of-market benefits, including:
 
-       Medical, Dental, and Vision insurance 
-       100% company paid premiums
-       Unlimited Paid Time Off
-       26 weeks of 100% paid Parental Leave (paternity and maternity)
-       401(k) plan with 6% employer matching
-       Generous company matching on donations to non-profit charities
-       Up to $20,000 tuition assistance toward degree programs, plus up to $4,000/year for ongoing professional education such as industry conferences
-       Plentiful snacks, drinks, and regularly catered lunches
-       Dog-friendly office (CAM office)
-       In-office gyms and showers (CAM, DC)
-       Bike sharing program memberships
-       Compassion leave and elder care leave
-       Mentoring and additional learning opportunities
-       Opportunity to expand professional network and participate in conferences and events 
 
About Kensho
Kensho uses machine learning, artificial intelligence, natural language processing and data visualization techniques to solve some of the hardest analytical problems and create breakthrough financial intelligence solutions for our parent company, S&P Global. 
 
Kensho was founded in 2013 by Harvard & MIT alums and was acquired by S&P Global in 2018. Kensho continues to operate as a startup in order to maintain our distinct, independent brand and to promote our breakthrough, innovative culture. Our team of Kenshins enjoy a dynamic and collaborative work environment that runs autonomously from S&P, while leveraging the unparalleled breadth and depth of data and resources available as part of S&P Global.  As Kenshins, we pride ourselves on maintaining an innovative culture that depends on diversity and inclusion.
 
We are an equal opportunity employer that welcomes future Kenshins with all experiences and perspectives. Kensho is headquartered in Cambridge, MA, with offices in New York City, and Washington D.C.  All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.
 

About Kensho

Kensho is a Data Analytics and Machine Intelligence Company Kensho deploys scalable machine learning and analytics systems across the most critical government and commercial institutions in the world to solve some of the hardest analytical problems of our time.

Want to learn more about Kensho? Visit Kensho's website.