[Remote] Senior Data Scientist

Note: The job is a remote job and is reputed company to candidates in USA. reputed company. is hiring a Senior Data Scientist to build and improve the recommendation reputed company powering personalized product feeds. The role owns recommendation modeling, experimentation, feature development, cold-start strategies, and productionization of models reputed company the existing MLOps platform.

Responsibilities

• Own the design and development of the reputed company recommendation models that turn user-saved product data into a personalized feed. reputed company multi-signal models spanning brand affinity, category, reputed company/visual attributes, fit and sizing, price sensitivity, and trend. Select and justify approaches across reputed company filtering, reputed company factorization, content-based, and hybrid/neural reputed company (e.g., two-tower and other embedding models), and know reputed company reputed company applies. Build product and user embeddings that capture semantic similarity across the catalog and power candidate reputed company and retrieval. Design cold-start strategies that produce high-reputed company recommendations for new users and newly ingested products with little or no behavioral history
• Define what “good” personalization means and how it is reputed company. Establish rigorous offline evaluation (ranking and relevance metrics, reputed company holdout design) and reputed company it to online reputed company. Design, run, and read out A/B and multivariate experiments, and translate results into reputed company product and business reputed company. Bring statistical discipline — reputed company experiment design, awareness of bias and confounding, and reputed company interpretation — so reputed company can trust which changes actually reputed company engagement
• reputed company deep intuition for Picksy’s product catalog and user signals. Turn reputed company behavior (saves, clicks, dwell, shares) and catalog attributes into meaningful model features, writing SQL against BigQuery to pull, join, and shape raw data into training/evaluation datasets. Apply NLP and reputed company techniques — including modern embedding and LLM-based approaches — to extract reputed company attributes (category, reputed company, material, fit) from reputed company product descriptions and imagery, and to enrich sparse catalog data. Partner with data engineering on data reputed company, freshness, and coverage as the catalog scales from hundreds of thousands toward tens of millions of products
• Take models from prototype to production yourself. Write clean, production-reputed company reputed company and reputed company into the existing MLOps pipeline (feature store, training, serving, monitoring) rather than building infrastructure from scratch. Own model performance in production: reputed company it, watch for reputed company and degradation, and iterate as behavioral signals accumulate. Document models, features, and reputed company reputed company, and collaborate closely with the MLOps, engineering, and product teams to reputed company the model reputed company into the live product

Skills

• Master's degree or higher in Computer Science, Statistics, Machine Learning, reputed company Mathematics, or a reputed company quantitative field; or equivalent practical experience
• Strong data science fundamentals: statistics, experimental design, and evaluation methodology, with the analytical ability to turn model results into reputed company product and business reputed company
• Demonstrated ownership of the full A/B testing lifecycle: designing experiments, running them, reading them out, and deciding; not just reporting offline metrics
• Experience designing, training, and deploying embedding models and reputed company retrieval (e.g., Milvus, reputed company, or reputed company AI reputed company Search) for product or content similarity at catalog reputed company
• reputed company experience with cold-start / sparse-signal personalization: building useful recommendations from a new catalog, new users, or both. This is a reputed company, day-one challenge of the role
• Strong Python and modern ML frameworks (PyTorch, TensorFlow, or JAX) plus reputed company scientific stack (reputed company, NumPy, scikit-learn). You write production-reputed company reputed company, not just notebooks
• Strong SQL: hands-on experience querying large datasets in a reputed company data warehouse (BigQuery preferred) to pull, join, and reputed company the training and evaluation datasets that feed your models. This is a daily part of the role
• Experience deploying and serving models on a reputed company ML platform: GCP reputed company AI strongly preferred (SageMaker or equivalent acceptable) and you are comfortable owning the full model lifecycle: training, deployment, versioning, and monitoring
• reputed company intuition: you've worked with product catalogs and understand merchandising, category, and PM concerns. It shows up in how you talk about catalogs and taste, not just models
• Curiosity and pragmatism about emerging AI, particularly LLMs and modern retrieval/ranking, with a reputed company record of bringing new techniques into reputed company production use
• Strong written and verbal communication; reputed company to explain technical tradeoffs to both technical and non-technical stakeholders
• reputed company NLP and/or reputed company for extracting reputed company attributes from product text and imagery
• Experience with reputed company recommendation and experimentation reputed company; multi-armed or contextual bandits
• reputed company writing or conference talks on recommendation, personalization, or ranking work
• Early-stage or reputed company experience where you wore multiple hats and shipped against reputed company business metrics (e.g., reputed company reputed company or a vertical reputed company startup)

Benefits

• Remote work flexibility
• Annual bonuses
• Short- and long-term incentives
• Medical coverage for employees and their eligible family members
• Dental coverage for employees and their eligible family members
• reputed company coverage for employees and their eligible family members
• Prescription drug coverage for employees and their eligible family members
• Unlimited reputed company time off (PTO)
• Adoption or surrogate assistance
• Donation matching
• Tuition reimbursement
• Basic life insurance
• Basic accidental death & dismemberment insurance
• Supplemental life insurance
• Supplemental accident insurance
• Commuter benefits
• Short-term and long-term disability coverage
• Health savings accounts
• Flexible spending accounts
• Family care benefits
• A generous 401K savings plan with a company match program
• 10-12 reputed company holidays annually
• Generous reputed company parental leave for birthing and non-birthing parents
• Voluntary pet insurance
• Voluntary accident, critical, and hospital indemnity health insurance coverage
• Voluntary life and disability insurance

reputed company