Staff Applied Scientist: Search & Recommendation Lead

Material Bank; United States; Hybrid; USD 140,000 - 210,000; Full time

Benefits offered by this job

Hybrid work model

Competitive benefits

Job summary

Material Bank is seeking a Staff Applied Scientist to lead the development of search and recommendation systems from inception to production. The role blends hands-on research with close collaboration with engineering to ship impactful improvements in a dynamic marketplace for materials.

You will design robust ranking and recommendation algorithms, explore diverse data sources, and advance query understanding to handle real-world, messy queries. Hybrid work and growth opportunities are offered.

Qualifications

• Proven track record building search, recommendations, or ranking systems that shipped to real users.
• Advanced degree in CS, ML, statistics, applied math, or equivalent hands-on experience.
• Deep understanding of search and recommendation systems: retrieval, ranking, relevance.
• Strong query understanding and NLP, including semantic and embedding-based retrieval.
• Real exploratory and experimental rigor: modeling, experimental design, hypothesis testing.
• Hands-on building ability; prototyping and implementing ideas.
• Experience deploying ML or data systems to production.

Responsibilities

• Improve search retrieval and ranking; design, tune, and evaluate how results are retrieved and ranked.
• Build our recommendation systems from the ground up; model member and project intent and surface recommendations across the experience.
• Explore data to determine strategies; run exploratory analyses on behavioral and catalog data.
• Apply advanced query understanding to messy, real-world queries, including long tail.
• Raise data quality by identifying and fixing catalog data issues.
• Do R&D you can ship: develop formulas, models, and re-ranking approaches and productionize.
• Iterate visual and color approaches for image-based search and color matching; assess suitability.
• Measure impact by building evaluation frameworks and running experiments as traffic grows.
• Collaborate with product, engineering, and catalog teams to ship improvements.

Skills

Search systems

Recommendations

Ranking

Query understanding

NLP

Experimental design

Prototyping

Production ML

Education

Advanced degree in quantitative field

Job description

Material Bank is seeking a Staff Applied Scientist to lead the development of search and recommendation systems from inception to production. The role blends hands-on research with close collaboration with engineering to ship impactful improvements in a dynamic marketplace for materials.

You will design robust ranking and recommendation algorithms, explore diverse data sources, and advance query understanding to handle real-world, messy queries. Hybrid work and growth opportunities are offered.