Kensho is a Machine Learning (ML) and Natural Language Processing (NLP) company, centered around providing cutting-edge solutions to meet the challenges of some of the largest and most successful businesses and institutions. We are owned by S&P Global and operate independently. Our toolkit illuminates insights by helping the world better understand, process, and leverage messy data. Specifically, Kensho’s solutions largely involve speech recognition (ASR), entity linking (NED), structured document extraction, automated database linking, text classification, and more.

Kensho’s AI Data Team is the data labeling component of the Machine Learning team - we build datasets for model training, evaluate model performance on real-world data, and manage an offshore team of data labelers. As a data specialist, you will collaborate with ML engineers to plan data annotation projects; extract, transform, and load data for those projects; work with our offshore annotation team to create high quality datasets; and analyze finished datasets. The ideal candidate is comfortable working with structured and unstructured data (preferably using Python), is able to collaborate with colleagues across Kensho and S&P, can solve problems independently and as a part of a team process, and is eager to learn new skills. 

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 (e.g., Cambridge, MA or NYC) will be required for team meetings or company events.

Kensho states that the anticipated base salary range for the position is 90k -125k. In addition, this role is eligible for an annual incentive bonus and potential equity plans. At Kensho, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case.

What You’ll Do:

• Collaborate with other ML teams at Kensho to plan data labeling projects: developing ontologies, drafting instructions, and establishing project timelines and milestones
• Extract, transform, and load data from a variety of sources into data labeling tools
• Monitor and assist our offshore data labelers as they label data, and review their annotations
• Create final datasets for ML teams once labeling is completed, and analyze the finalized data for trends and edge cases
• Assist with training and mentoring our offshore data labelers
• Assist with ad-hoc, high-visibility data projects as needed
• Auditing current labeling pipelines and practices, collaborating with ML Ops and ML Eng on model monitoring pipelines 
• A secondary focus of this role includes training and assigning our S&P auxiliary labeling team projects. The role may include onboarding S&P analysts onto our internal tool, distributing instruction sets, identifying and addressing edge cases, refining annotation guidelines, and pinpointing areas / cases where ML models struggle

What You'll Need:

• 2+ years of industry experience designing, building, evaluating, and maintaining robust datasets
• 0-1 years of management or mentorship experience
• Experience mentoring and/or building a team. We are looking for someone who can think long term about hiring and training
• Experience partnering and collaborating with product and technical teams 
• An innovation-oriented mindset and the ability to come up with out-of-the-box solutions
• A thoughtful and collaborative approach as a teammate
• Refined organizational skills and result-oriented attitude with superior attention to detail
• Measuring your professional success by your team’s success

Technology You'll Encounter:

• These languages and tools are ones that our team uses - or will eventually be using - on a regular basis. They are not prerequisites for successfully applying for this role, but demonstrated knowledge of some or all of these tools and languages - or a proven ability to quickly learn new tools and languages - will stand out.




• Data transformation and analysis: Python, Pandas, Numpy, Matplotlib 
• Deployment: Airflow
• Datastores: S3, SQLite
• Annotation tools: Labelbox

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)

- 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 is an Artificial Intelligence company that builds solutions to uncover insights in messy and unstructured data that enable critical workflows and empower businesses to make decisions with conviction.

Kensho was founded in 2013 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 Global, 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.