Data Analyst, New Graduate

Company Overview

Jobright.ai is an AI-driven job search platform that revolutionizes traditional job hunting by converting a solitary and time-intensive process into a streamlined, expert-supported experience. Its goal is to enhance every step of searching for jobs and speed up candidates' journey towards optimal employment matches.

Role Summary

As a Data Analyst with Jobright.ai, you will play a critical role in extracting and transforming data related to products, users, and the job market into meaningful insights. These insights will help refine search algorithms, improve recommendation systems, and elevate overall user satisfaction.

Key Responsibilities

• Examine diverse datasets including product, user behavior, and job market information to uncover trends and growth opportunities.
• Develop SQL queries and design varied reports, dashboards, and data workflows for continuous analysis.
• Establish and track essential product and business performance indicators.
• Assist in testing new features through experiments and assess their impacts on user engagement and business outcomes.
• Diagnose and resolve data quality challenges to boost reporting reliability.
• Effectively communicate analytical findings to teams across product, engineering, and business divisions.

Qualifications

Required:

• Recent graduates or soon-to-be graduates with a degree in Data Science, Statistics, Computer Science, Mathematics, Economics, or related disciplines.
• Proficient in SQL and familiar with Python programming or spreadsheet tools.
• Basic understanding of statistics, data analytics, and experiment design.
• Detail-oriented with strong analytical problem-solving abilities.
• Authorized to work remotely from within Canada.

Preferred:

• Hands-on experience with data analysis libraries such as pandas and scikit-learn, or visualization tools like Tableau and Looker.
• Knowledge of product analytics, recommendation engines, or search technologies.
• Experience handling large-scale or unstructured datasets.
• Background in internships, research, or practical analytics projects.