Data Analyst - SQL/Python (2-4 yrs)

Job Title : Data Analyst

Department : Tech

Location : Gurgaon, India

Employment Type : Full-time, On-site

Company Overview :

ZYOD was created with the vision of making building business easier in fashion and to make

quality fashion more accessible and affordable along with the motto of revolutionizing the fashion industry.

We are a Tech enabled manufacturing company that provides end-to- end design to delivery solutions to fashion brands with smooth tech integrations with the industry's fastest turnaround time and lowest MOQs.

As the most trusted clothing manufacturing company, we bring the latest styles and quality trends to provide you with the best as per your fast fashion needs. We have a team of experienced professionals who are passionate about fashion and committed to providing our clients with the best possible experience. We believe in providing our clients with a one-stop solution for all their fashion needs.
ZYOD has raised $18 million (Rs 150 crore) in its series A funding round. The investment was led by RTP Global, with participation from existing investors Lightspeed and Alteria Capital, as well as new investors Stride Ventures, Stride One, and Trifecta Capital.
Role Summary

The Data Analyst will be responsible for gathering, analyzing, and interpreting data to drive decision-making across the company's operations, from supply chain management to inventory forecasting, production optimization, and sales performance. The ideal candidate will have a strong background in Python, SQL, and data visualization, with the ability to turn data into actionable insights that improve business performance.

Key Responsibilities :

Data Analysis & Reporting :

- Analyze large datasets from various business units, including manufacturing, inventory, sales, and supply chain, to provide actionable insights.

Database Management :

- Use SQL to extract, manipulate, and manage data from company databases, ensuring data accuracy and availability.

Data Modeling :

- Develop and maintain data models for forecasting demand, optimizing inventory, and improving production efficiency.

Automation & Scripting :

- Utilize Python to automate data extraction, cleaning, and reporting processes. Build reusable scripts to streamline data workflows.

Visualization :

- Create and maintain dashboards and reports to visualize data trends using tools like Power BI, Tableau, or Python libraries such as Matplotlib and Seaborn.

Collaboration :

- Work closely with cross-functional teams including production, logistics, and sales to understand data needs and provide solutions that optimize operations.

Trend Analysis :

- Identify market trends, consumer preferences, and production bottlenecks to support strategic planning and improve business outcomes.

Quality Control :

- Ensure the integrity of data by performing quality checks, identifying discrepancies, and troubleshooting issues in a timely manner.

Key Requirements :

Education : Bachelor's degree in Data Science, Computer Science, Statistics, or a related field.

Experience :

- 2+ years of experience in data analysis, preferably within the fashion, manufacturing, or retail industries.

- Strong proficiency in Python and SQL for data manipulation and automation.

- Experience with data visualization tools like Tableau, Power BI, or similar platforms.

- Familiarity with manufacturing and inventory data models is a plus.

Skills :

- Advanced SQL skills for complex queries, data extraction, and reporting.

- Python programming skills for data cleaning, analysis, and process automation.

- Strong analytical mindset with the ability to solve problems and communicate insights effectively.

- Knowledge of fashion manufacturing processes and key business metrics is advantageous.

- Excellent written and verbal communication skills.

Preferred Qualifications :

- Experience in the fashion or manufacturing sector.

- Knowledge of supply chain and inventory management systems.

- Understanding of machine learning concepts and data science tools.

- Familiarity with ERP systems (e.g., SAP, Oracle).