
| Location: | Bangalore |
| Openings: | 1 |
| Salary Range: |
Description:
Key Responsibilities
- Collect, clean, and preprocess data from multiple sources to ensure quality and accuracy
- Perform exploratory data analysis (EDA) to identify trends, patterns, and opportunities
- Develop, evaluate, and optimize Machine Learning and Statistical Models
- Build and maintain ETL/ELT data pipelines for analytics and model development
- Collaborate with Product, Engineering, and Business teams to translate business problems into data solutions
- Monitor model performance and continuously improve accuracy and efficiency
- Present findings and recommendations to technical and non-technical stakeholders in a clear, concise manner
- Explore and implement emerging technologies in AI, Deep Learning, Generative AI, and Large Language Models (LLMs)
Required Skills
- Strong experience in Python, SQL, and Data Analytics
- Hands-on experience with Machine Learning algorithms and model evaluation
- Experience with data preprocessing, feature engineering, and EDA
- Knowledge of ETL/ELT processes and data pipeline development
- Experience with Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch
- Strong analytical, problem-solving, and communication skills
Preferred Skills
- Deep Learning, NLP, or Computer Vision
- Generative AI, LLMs, Prompt Engineering, or RAG
- Experience with cloud platforms (AWS, Azure, or GCP)
- Exposure to MLOps, model deployment, and monitoring
NOTE: Please find the feedback for Data Scientist (rejected candidates)
Quick feedback. Rather than general AI skills we need a candidate who is very strong in the following areas:
Optimization algorithms, integer programming, constraint programming, task assignment
Time series forecasting for demand forecasting
Machine learning: regression (wait times, preparation times), ETA prediction, travel time prediction etc
In other words, we need more traditional ML skills. Some domain knowledge in food tech or delivery use cases (Swiggy/zomato/blinkit/zepto) will be extremely valuable