Data Scientist

🕒 July 28

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Weekday (YC W21)

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2021

💼 Consulting

👥 HR Tech

☁️ SaaS

Consulting • HR Tech • SaaS

Weekday is a modern recruitment platform that combines AI technologies with a vast database of potential candidates, aiming to streamline the hiring process for companies in India. They offer various services, including a proactive outreach approach that helps employers connect with top talent, as well as tools for candidates to easily apply for jobs. Weekday's emphasis on candidate engagement through multiple channels, including email, WhatsApp, and phone calls, sets it apart in the competitive landscape of recruitment agencies.

📋 Description

• Design detailed, task-specific evaluation criteria for real-world data science deliverables, including: • - Data analyses • - Predictive and statistical models • - Dashboards and visualizations • - Experiment results • - Executive recommendations and business insights • Evaluate AI-generated and human-produced work using objective scoring frameworks. • Provide detailed written justifications for each evaluation, ensuring consistency and technical accuracy. • Apply sound analytical judgment to produce reproducible and defensible assessments. • Incorporate structured reviewer feedback and continuously refine evaluation methodologies. • Collaborate with cross-functional teams to improve AI training quality and evaluation standards.

🎯 Requirements

• 5+ years of professional experience in Data Science within an industry environment. • Strong background in business operations, product analytics, growth analytics, or similar data science functions at technology-driven organizations. • Deep expertise in: • - Experimental design and A/B testing • - Statistical analysis • - SQL and Python • - Metric development and performance measurement • - Translating analytical findings into business recommendations • Excellent written communication skills with the ability to clearly explain technical reasoning. • Exceptional attention to detail and the ability to evaluate work consistently against structured rubrics. • Comfortable receiving feedback and calibrating evaluation standards with peer reviewers. • Experience contributing to AI evaluation, model training, human feedback, or data annotation initiatives. (Preferred) • Familiarity with large language models (LLMs), AI-assisted analytics, or machine learning workflows. (Preferred) • Experience reviewing technical work or mentoring analytical teams is a plus. (Preferred)