Founded in 2021, Zepto has rapidly become one of India’s leading quick-commerce platforms. The company uses advanced technology, data science, and scalable logistics systems to deliver products efficiently across multiple cities.
Zepto has received strong backing from global investors and continues to scale rapidly in the Indian technology ecosystem. The company focuses heavily on innovation, operational efficiency, and customer-centric solutions.
About Zepto
Founded in 2021, Zepto has rapidly become one of India’s leading quick-commerce platforms. The company uses advanced technology, data science, and scalable logistics systems to deliver products efficiently across multiple cities.
Zepto has received strong backing from global investors and continues to scale rapidly in the Indian technology ecosystem. The company focuses heavily on innovation, operational efficiency, and customer-centric solutions.
Job Role: Data Scientist
The Data Scientist I role focuses on building machine learning models that improve real-time delivery time predictions. These models directly impact customer satisfaction by helping provide accurate delivery estimates.
This position is ideal for candidates who enjoy solving real-world problems using:
- Machine Learning
- Data Analysis
- Feature Engineering
- Predictive Modeling
- Real-time Systems
- Large-scale Data Processing
Key Responsibilities
Candidates selected for this role will work on advanced machine learning systems and predictive analytics projects. Some major responsibilities include:
1. Feature Engineering
Develop intelligent features using:
- Historical delivery data
- Spatial information
- Environmental signals
- Real-time operational data
2. Machine Learning Model Development
Build and optimize:
- Regression models
- Tree-based algorithms
- Predictive systems for delivery estimation
Popular algorithms mentioned include:
- XGBoost
- LightGBM
- Random Forest
3. Model Optimization
Work on:
- Hyperparameter tuning
- Feature selection
- Validation strategies
- Accuracy improvement
4. Real-Time Prediction Systems
Collaborate with engineering teams to deploy low-latency machine learning models into production systems.
5. Monitoring and Retraining
Monitor model performance, detect drift issues, and improve models continuously using retraining pipelines.
Required Skills
To succeed in this role, candidates should have strong fundamentals in:
Technical Skills
- Python Programming
- SQL
- Machine Learning Algorithms
- Statistics and Probability
- Data Analysis
- Regression Models
- Feature Engineering
Preferred Skills
Candidates with knowledge of the following technologies may have an advantage:
- PySpark
- Databricks
- Real-time ML Systems
- Spatial Data Processing
- A/B Testing
- Forecasting Models
Eligibility Criteria
Zepto is looking for candidates with:
- Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics, or related fields
- Strong understanding of machine learning concepts
- Knowledge of data-driven problem solving
Freshers with strong internships, academic projects, or practical machine learning experience are also encouraged to apply.
0–2 years of experience in Data Science, Machine Learning, or related roles
Why This Opportunity is Important for Freshers
Many companies ask for several years of experience before hiring for machine learning roles. However, this opportunity is valuable because Zepto is also encouraging freshers with strong project experience to apply.
If you have worked on:
- Machine learning projects
- Data science research
- Recommendation systems
- Predictive analytics
- NLP projects
- Real-world datasets
then this role could significantly boost your career.
How to Prepare for This Role
If you want to apply for this opportunity, focus on improving the following areas:
Strengthen Python Skills
Practice:
- NumPy
- Pandas
- Scikit-learn
- Data preprocessing
Learn SQL Properly
Understand:
- Joins
- Aggregations
- Window functions
- Query optimization
Build ML Projects
Create projects related to:
- Recommendation Systems
- Forecasting
- Classification Models
- Regression Models
Practice Model Evaluation
Understand concepts such as:
- Cross-validation
- Precision and recall
- RMSE and MAE
- Overfitting and underfitting
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