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Staff Data Scientist | Fraud / Billing

Machinify

Ort
Distans (US)
Arbetsplats
Distans
Anställningsform
Heltid
Lön
$180k–$230k
Publicerat
I dag
Källa
Himalayas
Ansök hos företaget
Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 85 health plans, including many of the top 20, and representing more than 270 million lives, Machinify brings together a fully configurable and content-rich, AI-powered platform along with best-in-class expertise. We’re constantly reimagining what’s possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs. We're hiring a Data Scientist focused on natural language processing to build models that turn unstructured text into product features and business insight. You'll own problems end-to-end — framing, data, modeling, evaluation, and shipping — and work closely with engineering and product to put your work in front of users. What you'll do - Design and train NLP models for tasks like classification, entity extraction, retrieval, summarization, and semantic search - Fine-tune and evaluate LLMs (open-source and API-based); build RAG pipelines and agentic workflows where appropriate - Build robust evaluation harnesses — offline metrics, human-in-the-loop review, and online A/B tests - Partner with ML engineers to productionize models (latency, cost, monitoring, drift detection) - Turn ambiguous product questions into well-scoped ML problems and communicate tradeoffs clearly to non-technical stakeholders What we're looking for - 3+ years of applied ML experience with a meaningful portion in NLP - Strong Python and the modern NLP stack: PyTorch or JAX, Hugging Face Transformers, spaCy, sentence-transformers - Hands-on experience fine-tuning transformer models (LoRA/QLoRA, instruction tuning, preference optimization) and/or building production RAG systems - Solid grounding in evaluation: knows the difference between BLEU/ROUGE/BERTScore/LLM-as-judge and when each is misleading - Comfortable with SQL, vector databases (pgvector, Pinecone, Weaviate, or similar), and one major cloud (AWS/GCP/Azure) - Clear written and verbal communication; can defend a modeling choice and also admit when a heuristic beats a model Nice to have - Publications at ACL/EMNLP/NAACL/NeurIPS or strong open-source contributions - Experience with multilingual NLP, speech, or multimodal models - Background shipping LLM features in a regulated domain (healthcare, finance, legal) What We Offer - Work from anywhere in the US! Machinify is digital-first. - Top Medical/Dental/Vision offerings - FSA/HSA - Tuition reimbursement - Competitive salary, 401(k) with company match - Unlimited PTO - Additional health and wellness benefits and perks - Flexible and trusting environment where you’ll feel empowered to do your best work The salary for this position is based on an array of factors unique to each candidate: Such as years and depth of experience, set skills, certifications, etc. We are hiring for different levels and the base salary can range from $180k-$230k+ based on your assessed level. Compensation also includes meaningful equity, healthcare, unlimited PTO, and more. Equal Employment Opportunity at Machinify We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace. Machinify is an employment at will employer. We participate in E-Verify as required by applicable law. In accordance with applicable state laws, we do not inquire about salary history during the recruitment process. If you require a reasonable accommodation to complete any part of the application or recruitment process, please let our recruiters know. See our Candidate Privacy Notice at: Originally posted on Himalayas

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