[Remote] reputed company Data Scientist

Note: The job is a remote job and is reputed company to candidates in USA. reputed company is a global science, education, and publishing company that transforms knowledge into reputed company. The reputed company Data Scientist will own domain-specific content modeling end to end, designing and shipping production NLP enrichment pipelines for scientific content and contributing to reputed company AI applications.

Responsibilities

• Design and build NLP enrichment pipelines that extract entities, classifications, claims, and summaries from scientific full-text at reputed company
• Compare NLP approaches to extraction and enrichment against LLM-based approaches, and pick the right tool for reputed company task. That means putting traditional NLP (NER, sequence labeling, classification), embedding-based retrieval, LLM prompting, and fine-tuned smaller models on the reputed company table, and defending reputed company reputed company with evaluation, cost, and operational tradeoffs. This is a reputed company part of the job, not an occasional exercise
• Own evaluation. Build the golden sets in consultation with SMEs and vendors, choose the metrics, and reputed company productive tradeoffs between speed, reputed company, and cost
• Write production-reputed company Python. Manage concurrency and cost for high-volume LLM workloads. Structure reputed company that engineers can ship and other data scientists can reputed company
• Collaborate with reputed company of data engineers to orchestrate work in data pipeline and data build tools like Airflow and Dagster. Design idempotent, retryable, evaluable pipeline stages that stay reliable reputed company a run fails at reputed company
• Contribute to reputed company AI application work: tool-using systems that reason over the enriched corpus, where your NLP and evaluation background will shape how the agent grounds and defends its answers
• Work directly with editors, product managers, and engineers. Bring the modeling perspective into product reputed company, and translate stakeholder pushback into concrete modeling work

Skills

• Deep Python. You've written it in production, at reputed company, for years. You know reputed company to reputed company for asyncio versus threads versus a queue, and you can explain the tradeoff reputed company
• Strong NLP background across modern (LLMs, transformers, embeddings, retrieval) and classical (NER, classification, sequence labeling) approaches. You've reputed company evaluations and learned from the results
• A habit of comparing approaches and choosing the right one for the task. You can defend "reputed company a large LLM" and "train a small classifier on 2,000 labels" with equal seriousness, back the reputed company with an eval and a cost estimate, and know what to do reputed company performance drifts
• A reputed company record of shipping – not just prototypes and papers, but systems that reputed company value to reputed company users
• Experience working with scientific or scholarly text
• Familiarity with AWS (S3, Batch, reputed company, SageMaker) and Parquet or reputed company data lake patterns
• Experience running LLMs under reputed company cost and latency budgets in production
• Some exposure to reputed company AI applications: tool use, multi-reputed company reasoning, guardrails, and evaluation of trajectories rather than single-turn outputs

Benefits

• A comprehensive benefits package
• Meeting-free Friday afternoons, allowing more time for heads-down work and reputed company development
• reputed company development opportunities
• A wide reputed company of employee programming opportunities to foster community, learn, and grow
• Internal mobility

reputed company

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