Data Analyst / Data Scientist

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August 8

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Weekday (YC W21)

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Human Resources • SaaS • Recruitment

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.

11 - 50 employees

Founded 2021

☁️ SaaS

🎯 Recruiter

📋 Description

• This role is for one of the Weekday's clients • Salary range: Rs 300000 - Rs 1200000 (ie INR 3-12 LPA) • Min Experience: 1 years • Location: Remote (India) • JobType: full-time • We’re looking for a passionate and detail-oriented Data Analyst / Data Scientist to join our growing analytics team. • This role is perfect for someone who thrives on solving complex problems using data, loves diving deep into datasets, and has a strong command of analytical tools and programming languages. • As a Data Analyst / Data Scientist, you will play a crucial role in helping teams make data-driven decisions by uncovering actionable insights from structured and unstructured data. • You’ll work closely with stakeholders across departments—such as product, marketing, and operations—to understand their challenges and deliver meaningful analysis and visualizations that guide strategy and execution.

🎯 Requirements

• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related field. • 1–5 years of experience in a data analyst or data scientist role, preferably in a fast-paced or startup environment. • Strong proficiency in SQL and Python for data manipulation and analysis. • Experience building dashboards and visualizations using Tableau (or similar tools such as Power BI or Looker). • Solid understanding of statistical methods and ability to apply them to real-world business problems. • Strong analytical and problem-solving skills with attention to detail and accuracy. • Excellent communication and collaboration skills, with the ability to present findings in a clear and concise manner. • Nice to Have: • Exposure to machine learning techniques and libraries (e.g., scikit-learn, XGBoost, etc.). • Experience working with cloud-based data platforms (AWS, GCP, or Azure). • Familiarity with version control tools like Git and workflow automation tools like Airflow.