– DATA SCIENTIST

Company: Orlin Apparel Private Limited

Position: Data Scientist

Department: Data Science / Business Analytics / IT

Industry: Textile & Apparel / Fashion / E-commerce

Location: Surat, Gujarat

Employment Type: Full-Time

Experience: 2–5 Years

Reports To: Head – IT / Business Head / Management

1. Job Summary

Orlin Apparel Private Limited is looking for a Data Scientist who can use data, statistical analysis, Artificial Intelligence, and Machine Learning to solve business problems and improve decision-making across fashion design, production, inventory, sales, e-commerce, marketing, and supply chain operations . The candidate will be responsible for collecting and analyzing business data, developing predictive models, creating dashboards and insights, and implementing data-driven solutions to improve sales, inventory planning, customer understanding, and operational efficiency.

1. Key ResponsibilitiesA. Data Collection & Analysis

- Collect, clean, validate, and analyze data from ERP, OMS, e-commerce platforms, Excel, databases, and other business systems.
- Combine data from sales, inventory, production, procurement, marketing, warehouse, and customer sources.
- Identify trends, patterns, anomalies, and business opportunities.
- Ensure data quality, consistency, and accuracy.

B. Sales & Demand Forecasting
- Develop models to forecast sales and product demand.
- Forecast demand at SKU, category, size, color, season, and channel level .
- Analyze historical sales, seasonality, promotions, pricing, and customer behavior.
- Support management in deciding which products and quantities should be produced or stocked.
- Monitor forecast accuracy and continuously improve forecasting models.

Demand forecasting and product-level forecasting are particularly relevant in apparel because data science can help determine collection, inventory, and channel decisions. C. Inventory & Supply Chain Analytics
- Develop data-driven solutions for inventory optimization.
- Identify fast-moving, slow-moving, and non-moving products.
- Analyze stock-outs, excess inventory, sell-through, and inventory turnover.
- Support replenishment planning.
- Identify opportunities to reduce excess and obsolete stock.
- Develop predictive models for inventory requirements.

D. E-commerce Analytics
- Analyze sales data from platforms such as Amazon, Flipkart, website, and other marketplaces used by the company .
- Analyze product performance and SKU-level sales.
- Monitor conversion rate, average order value, returns, cancellations, RTO, and customer behavior.
- Identify high-performing and low-performing products.




- Develop models to predict product demand and customer purchase behavior.
- Provide data-driven recommendations for e-commerce growth.

E. Customer & Marketing Analytics
- Analyze customer purchasing behavior and preferences.
- Develop customer segmentation models.
- Identify repeat customers and potential high-value customers.
- Analyze campaign and advertisement performance.
- Support personalized product and promotion recommendations.
- Measure marketing ROI and customer acquisition performance.

F. Product & Fashion Analytics
- Analyze performance by:
- Product category
- Style
- Color
- Size
- Fabric
- Price range
- Collection
- Season
- Identify emerging product trends from historical and current sales data.
- Provide insights to Fashion Design, Merchandising, and Product Development teams.
- Support data-driven collection planning.

G. AI & Machine Learning
- Develop and implement ML models for business use cases.
- Apply appropriate techniques such as:
- Regression
- Classification
- Clustering
- Time-Series Forecasting
- Recommendation Systems
- Anomaly Detection
- Predictive Analytics
- Explore Generative AI/LLM applications where they can create measurable business value.
- Automate repetitive analytical and reporting activities.

H. Dashboard & Business Reporting
- Develop dashboards and analytical reports using Power BI / Tableau / Python / Excel .
- Create management dashboards for:
- Sales
- Inventory
- E-commerce
- Production
- Marketing
- Customer analytics
- Demand forecasting
- Convert complex data into simple and actionable business insights.
- Present findings to management and department heads.

I. Model Development & Deployment
- Define business problems and convert them into data science projects.
- Perform exploratory data analysis.
- Build, test, validate, and optimize models.
- Monitor model performance after deployment.
- Work with IT/Data Engineering teams to integrate models into business applications.

End-to-end ownership—from problem definition and data preparation through model development, validation, deployment, and business implementation—is a standard expectation for modern apparel/retail data-science roles.
1. Key Projects Expected at Orlin

The Data Scientist may work on projects such as:
1.



SKU-wise Sales Forecasting
2. Demand Forecasting for New Collections

3. Inventory Optimization
4. Stock-Out Prediction
5. Slow-Moving Stock Prediction
6. E-commerce Sales Prediction

7. Customer Segmentation

8. Product Recommendation System

9. Return/RTO Prediction
10. Price & Promotion Analytics
11. Marketing Campaign Performance Prediction

12. Production Demand Planning
13. Sales Trend & Seasonality Analysis
14. Automated MIS & Management Dashboards
15. AI-based Business Process Automation

16. Required Technical SkillsProgramming

- Python – Mandatory
- Pandas
- NumPy
- Scikit-learn
- Matplotlib / Seaborn
- Basic PyTorch or TensorFlow preferred

Database
- Strong SQL knowledge
- Data extraction and transformation
- Database management concepts

Machine Learning
- Regression
- Classification
- Clustering
- Decision Trees
- Random Forest
- XGBoost
- Time-Series Forecasting
- Model Evaluation
- Feature Engineering

Data Visualization
- Power BI / Tableau
- Advanced Excel
- Dashboard development
- Data storytelling

Advanced / Preferred Skills
- NLP
- Generative AI / LLM
- Recommendation Systems
- Deep Learning
- MLOps
- Cloud platforms such as AWS, Azure, or GCP

Current apparel-focused Data Scientist roles commonly emphasize Python, SQL, ML, forecasting, optimization, and deployment, with GenAI/cloud/MLOps as additional skills.
1. Educational Qualification

- Bachelor's or Master's degree in:
- Data Science
- Statistics
- Mathematics
- Computer Science
- Artificial Intelligence
- Machine Learning
- Engineering
- Economics or a related quantitative field

Preferred: M.Sc. / MCA / M.Tech / MBA Analytics / PG in Data Science or equivalent.

1. Experience

2–5 years of relevant experience in Data Science, Machine Learning, Business Analytics, E-commerce Analytics, Retail Analytics, or a related field. Experience in Fashion, Apparel, Textile, Retail, E-commerce, or Manufacturing will be an added advantage.

1. Key Competencies

- Strong analytical and problem-solving ability
- Business-oriented thinking
- Strong statistical understanding
- Good communication and presentation skills
- Ability to explain technical results to non-technical teams
- Attention to data accuracy and detail
- Ability to work independently and cross-functionally
- Solid curiosity and continuous-learning mindset

1. Key Departments for Coordination

The Data Scientist will work closely with:
- Management
- Sales
- E-commerce
- Marketing
- Fashion Design
- Merchandising
- Production
- Planning
- Inventory / Warehouse
- Procurement
- Finance / Accounts
- IT / Data Engineering

📌 Data Scientist (Surat)
🏢 Orlin Apparel
📍 Surat