Data Scientist

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Weekday (YC W21)

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2021

☁️ SaaS

🎯 Recruiter

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.

📋 Description

• Transform complex distributor transaction data into actionable sales opportunities. • Develop predictive models, recommendation engines, and commercial analytics solutions that directly influence sales strategies and revenue growth. • Work with large-scale B2B datasets containing thousands of customers, products, SKUs, and branch locations. • Turn raw ERP data into meaningful insights, dashboards, and opportunity recommendations for commercial teams and business leaders. • Support sales teams, executive decision-making, and business growth initiatives.

🎯 Requirements

• 6+ years of experience in Data Science, Analytics, or Machine Learning roles. • Strong experience working with B2B commercial datasets involving customers, products, transactions, and sales data. • Proven experience developing: • Recommendation systems • Market basket analysis models • Propensity and predictive analytics models • Advanced proficiency in Python and SQL. • Experience handling large-scale transactional datasets with millions of records and extensive product catalogs. • Hands-on experience working with ERP-generated data and complex commercial data structures. • Strong analytical thinking and problem-solving capabilities. • Ability to communicate technical concepts effectively to business stakeholders. • Experience with ERP platforms such as Prophet 21, Eclipse, Kinetic, or similar enterprise systems. • Background in distribution, wholesale, manufacturing, industrial products, retail analytics, or B2B commerce. • Experience building analytics solutions around SKU-level purchasing behavior. • Knowledge of recommendation engines and customer analytics in B2B environments. • Hands-on experience with Power BI, Tableau, or similar visualization tools. • Familiarity with data quality challenges including duplicate records, inconsistent hierarchies, and fragmented transactional data.