Senior Applied Scientist

Job not on LinkedIn

🔥 1 hour ago

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🧬 Research Scientist

👻 Ghost score 15%

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The Krazy Coupon Lady

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2009

🤲 Charity

🌍 Social Impact

Charity • Social Impact

The Krazy Coupon Lady Foundation is the nonprofit 501(c)(3) arm of The Krazy Coupon Lady that provides direct financial support and donated items to refugees located in Ada County, Idaho. For over nine years KCLF has helped hundreds of refugees and annually donates to 1,000+ individuals, distributing more than $350,000 in aid each year and serving people from over 50 countries. The organization focuses on resettlement support and community assistance through donations and local services based in Boise, ID.

📋 Description

• Design, develop, and apply machine learning solutions for personalization across recommendation, retrieval, and ranking • Translate ambiguous requests into scalable models and execute experiments to deliver production-ready capabilities • Deliver end-to-end scientific work spanning problem formulation, exploration, model development, experimentation, and deployment • Partner with platform engineering and product to integrate machine learning solutions into services and workflows • Participate in system design and data modeling • Select appropriate methods and validate outcomes to improve model performance • Contribute technical expertise to improve scientific and engineering quality • Design, build, and own feature engineering pipelines • Collaborate with data engineering to iterate on data models supporting feature engineering pipelines • Own statistical measurements, conduct custom tests or use analytics tools, and present readouts to senior non-technical audiences • Author white papers, technical blog posts, and conference submissions showcasing KCL’s applied science work

🎯 Requirements

• MS or PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, or a related quantitative field • 5+ years of applied machine learning experience delivering models to production • In-depth knowledge of modern recommendation, retrieval, and ranking, including dual-encoder retrieval, transformer-based sequence models, and learning-to-rank • Strong programming skills in Python, with hands-on experience in PyTorch or TensorFlow • Experience running offline evaluation and online experimentation • Publications in recommendation conferences or comparable body of applied output (preferred) • Experience with cold start recommendation, content-based or contextual models, and ephemeral item catalogs (preferred) • Experience with session-based or sequential recommendations for anonymous or lightly-identified users (preferred) • Experience with multi-objective optimization or constrained ranking (preferred)

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