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Senior Data Scientist

PendoFull-time$160k - $190kNew York City, New York; Raleigh, North CarolinaMay 20, 2024

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Team Description

The Machine Learning Group at Pendo is dedicated to enhancing Pendo’s product suite by delivering actionable insights and reliable predictions that our customers trust and value. Our team is highly committed to adopting excellent research and development practices while maintaining a keen understanding of the customer's perspective, ensuring that our solutions are both technically robust and aligned with their needs.

Our solutions include diverse focus areas, from classical ML algorithms to cutting-edge Generative Models. By combining qualitative and quantitative data, we take projects from initial ideation to production. As we strive to explore the boundaries of what is possible in the realm of machine learning, we aim to disrupt the way people build and use software and deliver the ultimate value to Pendo’s customers. **This role can either sit at our HQ Office in Raleigh, NC (301 Hillsborough St.) or our office in New York City (28 West 25th St.) 

Role Responsibilities 

  • Define the project scope and set success criteria together with the Product team.
  • Explore data, formulate and present POCs (Proof of Concepts).
  • Develop, measure, and deploy models to production, monitor them, and understand the customer experience and the gaps.
  • Contribute to our ML infrastructure by designing and implementing scalable machine learning pipelines with the team’s MLEs (Machine Learning Engineers).
  • Continuously explore new technologies and tools that can be harnessed for our mission to improve the customer experience.

Minimum Qualifications 

  • M.Sc. or Ph.D. degree in Computer Science, Statistics, Mathematics, Physics, or a related field
  • 5+ years of hands-on experience in developing and delivering ML components to production at scale
  • Deep understanding of machine learning theory and algorithms - supervised, unsupervised, generative AI, RAG architecture
  • Ability to break a business problem into ML components
  • Production-grade development skills in Python and experience with machine learning libraries (Scikit-learn, etc.).
  • A good command of software engineering best practices

Pendo Description:

Pendo was founded in 2013 by former product managers, who combined their heads and hearts to build something they wanted but never had as product managers -- a simple way to understand and attack what truly drives product success.  Our mission is to improve society's experience with software.

Come join one of the fastest-growing startups, supported by best-in-class institutions like Battery Ventures, Salesforce Ventures, Spark Capital and Meritech. You will gain experience in a diverse and exciting set of technologies and clients and have a real impact on Pendo's future. Our culture is passionate, dynamic, and fun.

EEOC

We are an equal opportunity employer and believe having diverse teams where everyone brings their whole self to Pendo is key to our success. We welcome all people of different backgrounds, experiences, abilities and perspectives.

Accessibility

Pendo is committed to working with, and providing access and reasonable accommodation to, applicants with mental and/or physical disabilities. If you think you may require an accommodation for any part of the recruitment process, please send a request to: [email protected]. All requests for accommodations are treated discreetly and confidentially, as practical and permitted by law.

Compensation

Our salary ranges are based on paying competitively for our size and industry, and are one part of many compensation, benefits and other reward opportunities we provide.

The expected salary range for this role to be performed in North Carolina is $160,000 - $175,000.

The expected salary range for this role to be performed in New York is $175,000 - $190,000.

Individual pay rate decisions, including offers made within and over the expected salary range, are based on a number of factors, including qualifications for the role, experience level, skillset, and balancing internal equity relative to peers at the company.

 

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