Posh is looking to build the foundation of their personalization and recommendation system to address the loss of human connection in digital platforms and drive real-world connections.
Requirements
- Possesses 5+ Years of full time Data Experience: Has at least 5 years of hands-on experience in data science or analytics engineering. Demonstrates a strong ability to design, build, and optimize scalable data systems.
- Expert in SQL and Python: Demonstrates strong proficiency in SQL and Python, with deep experience cleaning data, engineering features, and building efficient, production-ready modeling pipelines.
- Strong Ability to Analyze and Evaluate Models: Skilled in designing experiments, interpreting model performance, and communicating insights clearly to both technical and non-technical stakeholders.
- Experience Building Personalization and Recommendation Systems: Has built or contributed to ranking, classification, recommendation, or personalized user experience models in production environments.
- Proficient with Modern Data and ML Tooling: Experienced working with cloud data platforms and analytics tooling, and familiar with best practices in data modeling, pipeline reliability, and ML optimization.
- Has a Background in Early Stage Data Team (Required): Exhibits high interest in startups and has experience building the early foundation of a data team at a small tech company.
- Cloud ML Tools & Consumer Scale (Bonus): Experience with AWS Personalize, SageMaker, or similar cloud ML platforms, and/or working on consumer-facing products operating at scale.
Responsibilities
- Designing and Preparing High-Quality Data for Personalization Models: Own the process of data cleaning, feature selection, and model selection to build a high-performing personalization model. Ensure all inputs into personalization algorithms are reliable, well-structured, and optimized for downstream ML performance.
- Building and Maintaining Scalable Pipelines for Modeling Data: Develop robust ETL/ELT pipelines that transform raw behavioral, transactional, and catalog data into features for recommendation systems. Continuously iterate to improve data freshness and coverage using SQL and Python.
- Optimizing Infrastructure to Support ML Personalization at Scale: Enhance data architecture and processing frameworks to support real-time and batch modeling needs.
- Ensuring Strong Data Governance and Documentation: Implement best practices for data quality, documentation, observability, and lineage across all model-bound datasets.
- Collaborating with Product and Engineering on Instrumentation & Feature Tracking: Work closely with Engineering to ensure accurate tracking and logging of user actions and product interactions needed for personalization systems. Partner with Product to translate business needs into feature definitions and modeling requirements.
- Optimizing Classification Models: Develop, refine, and optimize classification models that accurately categorize events. Improve signal quality through feature engineering, tuning, sampling, and continuous iteration to ensure accurate tagging that powers downstream personalization algorithms.
Other
- This is an in-person position at our New York City office, located in the heart of SoHo.
- If you're passionate about building from 0 to 1 and making a lasting impact, this is the role for you.
- Posh provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
- This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
- Posh is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. Please let us know if you need assistance or accommodation due to a disability
