Senior Applied Scientist Nlp at Kensho

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

Kensho is seeking a Senior Machine Learning Scientist to join our NLP Team, a product and research organization applying and extending the state of the art of textual and document-based AI across a variety of domains. The ideal candidate has deep industry or research experience and is a recognized expert in one or more core NLP fields, for example:

- Named entity recognition (NER)
- Entity linking and coreference resolution
- Extreme multiclass text classification
- Open-domain question answering
- Relationship and fact extraction
- Summarization


What You’ll Do

Develop novel NLP algorithms and models using state-of-the-art techniques like deep learning and knowledge base-augmented ML
Move the needle on unsolved problems in cross-domain NLP by conducting original research into replicating and augmenting human expert behavior with machine intelligence
Write production-ready modeling code that can be scaled out to billions of documents and millions of users
Contribute to a stellar engineering culture that values simplicity and function rooted in excellent design, documentation, testing, and code
Collaborate with senior product and engineering leaders to identify the most promising problems to go after
Share your results with your colleagues (presentations), senior executives (board meetings), and the world (published papers, patents, and blog posts)
Mentor and lead other ML Scientists and Engineers to help make our team even more awesome!



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:

You hold a degree in Computer Science, Applied Math, or a similar field
You have experience designing, executing and evaluating ML experiments with real-world applications
You have mastery of the techniques required to work effectively with real-world data and have developed a successful track record training ML models on large, messy datasets
You have a deep understanding of what makes for well engineered software systems and understand that even superlative ML coupled with poor code will not go far
You prefer to collaborate iteratively on hard problems with your teammates rather than spending stretches of time working alone and presenting your results intermittently
You have a love for learning new skills and domains and share your knowledge freely, proactively, and effectively with others who are interested
You are a generous and fun teammate and can take your work seriously without taking yourself too seriously



Technologies We Love


ML: Pytorch, Hugging Face, Weights & Biases

Deployment: Airflow, Docker, 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.