Lead Data Scientist, AI Labs

OVERVIEW

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Across our organization were building a workplace where collaboration is essential diverse voices are heard and inclusion is the key to our success. We are committed to doing the right thing in our journalism and in every role at NPR.This means that integrity adherence to our ethical standards and compliance with legal obligations are fundamental responsibilities for every employee at NPR.

As the Lead Data Scientist for the AI Labs team you will serve as the technical and ethical anchor for NPRs artificial intelligence initiatives. You will lead data science expertise for a content metadata overhaul to power new audience-focused personalization engines. Rather than building models from scratch you will focus on fine-tuning evaluating and scaling existing foundational models as well as deploying machine learning algorithms for public media.. You will collaborate extensively across the organization to align architectures ensure secure cloud deployments and protect intellectual property. This position demands a high focus on accuracy journalistic ethics data privacy and responsible scaling.

• Lead the selection fine-tuning and optimization of open-source and proprietary LLMs tailored to NPRs unique content voice.
• Design and architect automated machine learning pipelines to transform decades of unstructured audio transcripts and text to support automated semantic metadata generation.
• Collaborate with the product design and engineering teammates to translate user needs into production-ready data science workflows.
• Architect recommendation frameworks that leverage enriched metadata to drive deep style-based audience personalization while preserving editorial curation.
• Partner with Data Products to construct clean self-service data pipelines and audience analytics models inside BigQuery.
• Support newsroom research through the prototyping validation and development of API-driven tooling and secure database search models.
• Establish strict evaluation testing and benchmarking frameworks to guarantee model outputs meet NPRs standards for factual accuracy and neutrality.
• Proactively identify audit and mitigate algorithmic bias in metadata generation and audience discovery systems.
• Ensure all AI applications scale securely and cost-effectively balancing computational efficiency with rigorous data privacy guardrails.
• Collaborate with growth and data platforms to leverage content metadata for user lifecycle retention and smart audience segmentation.

The above duties and responsibilities are not an exhaustive list of required responsibilities duties and skills. Other duties may be assigned and this job description is subject to change at any time.

• 8 years of professional experience in Data Science Machine Learning or Natural Language Processing (NLP) shipping production-grade systems.
• Proven track record of applying fine-tuning and evaluating Large Language Models (LLMs) and foundational architectures.
• Experience with Automatic Speech Recognition (ASR) diarization and audio preprocessing pipelines.
• Demonstrated experience designing and maintaining large-scale data architectures vector databases and semantic search pipelines.
• Hands-on experience designing deploying and optimizing production-grade recommendation engines or personalization systems at scale.
• Practical hands-on experience building machine learning workflows within major cloud environments (Azure AWS or GCP).
• Experience successfully navigating matrixed cross-disciplinary collaboration between technical engineering teams and non-technical stakeholders.
• Ability to identify common AI pitfalls such as hallucinations or formatting errors and design robust algorithmic workarounds.

• Experience working with large volumes of unstructured multimedia digital audio processing or automated speech-to-text workflows.
• Prior experience working within a media organization digital newsroom or public service institution.
• Experience integrating automated LLM evaluation gates and regression testing directly into CI/CD deployment pipelines

• Deep technical expertise in Python ML and agentic engineering frameworks vector search engines and two-stage retrieval architectures.
• Strong proficiency in SQL and cloud data warehouse ecosystems (such as BigQuery or Snowflake).
• Deep understanding of Retrieval-Augmented Generation (RAG) patterns and semantic search tools.
• Professional-level familiarity with model evaluation methodologies prompt engineering techniques and API integration workflows.
• Strong commitment to algorithmic ethics data privacy compliance and methods for identifying or mitigating bias.

• Advanced degree (PhD preferred) in Computer Science Data Science or Machine Learning
• Advanced academic research in relevant fields

• Hybrid Permitted:
  • This is a hybrid permitted role. Some aspects of this role require duties better performed at an NPR facility. The employee will be required to be in the office at the Washington D.C. or New York City location at least two to three days per week.

• This is a full-time exempt position.

Salary Range: The U.S.-based anticipated salary range for this opportunity is $164000 $201000 plus benefits. The range displayed reflects the minimum and maximum salaries NPR expects to provide for new hires for the position across all US locations.

NPR Benefits: NPR provides comprehensive benefits for employees and dependents. Regular full-time employees scheduled to work 30 hours or more per week are eligible to enroll in NPRs benefits options. Benefits include access to health and wellness paid time off and financial well-being. Plan options include medical dental vision life/ accidental death and dismemberment long-term disability short-term disability and voluntary retirement savings to all eligible NPR employees.

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NPR is an Equal Opportunity Employer. NPR is committed to being an inclusive workplace that welcomes diverse and unique perspectives all working toward the same goal to create a more informed public. Qualified applicants receive consideration for employment without regard to race color ethnicity national origin ancestry age religion religious belief sex (including pregnancy childbirth and related medical conditions lactation and reproductive health decisions) sexual orientation gender gender identity or expression transgender status gender non-conforming status intersex status sexual stereotypes nationality citizenship status personal appearance marital status family status family responsibilities military status veteran status mental and physical disability medical condition genetic information genetic characteristics of yourself or a family member political views and affiliation unemployment status protective order status status as a victim of domestic violence sexual assault or stalking or any other basis prohibited under applicable law.

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