Posted in: Other in San Francisco | Posted: |
About The Role
As a key member of our team, your primary responsibility is to become a domain expert in evaluating recommender systems. This role demands a blend of data science expertise, technical prowess, and effective communication skills. Additionally, you will collaborate with the Rubber Ducky Labs team to develop tools that streamline the analysis of recommender systems.
Requirements
Example Job Responsibilities Include
Collaborating with executives and machine learning engineers to design comprehensive metrics for evaluating online recommender systems.
Utilizing clustering and segmentation techniques to categorize users within a recommender system.
Actively engaging with the Rubber Ducky Labs product, providing valuable feedback to enhance its performance.
Conducting internal tech talks and crafting documentation to educate teammates on recommender systems concepts.
Directly interfacing with customers to gather insights and address their needs.
Our Tech Stack
Frontend: React, Typescript, Mantine, Chart.js
Backend: Python, Fast API, SQLAlchemy, Postgres
Infrastructure: Docker, AWS
Data Analysis: Python, Jupyter Notebooks, pandas, scikit-learn
Minimum Requirements
2+ years of industry experience in a data science or data analyst role
Prior experience in evaluating production recommender systems, search engines, or information retrieval systems
Ability to navigate ambiguous requirements and derive actionable insights
Proficiency in SQL and willingness to explore new databases and data analytics systems
Sound knowledge of machine learning, data science, statistics, and data visualization
Strong communication skills and a growth mindset
Preferred Qualifications
Experience engaging directly with executive-level stakeholders
Track record of sharing work and knowledge through platforms like blog posts, meetups, or conference talks
Benefits
Competitive salary + substantial equity for founding engineers
Comprehensive health benefits package (medical, dental, vision)
Flexible work-from-home policy, with the option to work remotely up to 3 days a week
Please note that visa sponsorship is not available for this position.