Backend Developer Python / Machine Learning

Experience: 48 years

Primary Skills: Python, Classical Machine Learning, Forecasting, ML Model Development, REST APIs

Technical Skills

- Strong hands-on experience with Python 3.x
- Strong programming and problem-solving skills
- Ability to write Python programs from scratch without relying heavily on built-in functions
- Good understanding of time and space complexity
- Experience with FastAPI / Flask and development of REST APIs
- Strong knowledge of Pandas, NumPy and SQLAlchemy
- Experience with scikit-learn and classical machine learning techniques
- Strong understanding of:
- Linear Regression
- Logistic Regression
- Decision Trees
- Random Forest
- XGBoost
- LightGBM
- CatBoost

- Hands-on experience with classification and regression problems
- Robust understanding of ML evaluation metrics including:

- Accuracy
- Precision
- Recall
- F1 Score
- ROC-AUC
- MAE
- MSE
- RMSE
- R

Forecasting / Time Series

- Hands-on experience in forecasting and time-series machine learning
- Understanding of:
- Time-series data preparation
- Feature engineering
- Lag features
- Rolling statistics
- Train/test split for time-series data
- Forecasting evaluation

- Experience with classical forecasting/ML techniques such as:

- Linear Regression
- Random Forest
- XGBoost
- ARIMA/SARIMA or similar forecasting approaches

- Ability to select appropriate forecasting algorithms based on business requirements and data characteristics

Machine Learning Engineering

- Understanding of the end-to-end machine learning lifecycle
- Model development, training, validation and deployment
- Model performance monitoring
- Data drift and model drift monitoring
- Data quality and validation frameworks
- Handling:
- Missing data
- Outliers
- Feature drift
- Class imbalance
- Data leakage





- Experience with model retraining and performance monitoring strategies
- Understanding of A/B testing and experimentation

Advanced ML / Architecture

- Experience designing and implementing ML solutions for real-world business problems
- Understanding of ensemble learning and gradient boosting
- Ability to explain algorithm selection and trade-offs
- Experience integrating business/engineering rules with ML predictions
- Understanding of probabilistic vs. deterministic decision frameworks
- Experience handling complex ML problems such as:
- Class imbalance
- Correlated features
- Spatial/temporal dependencies
- Model interpretability

- Experience designing scalable ML/analytics pipelines

Backend / Cloud / DevOps

- Experience developing Python-based microservices and REST APIs
- Experience with FastAPI/Flask
- Docker/containerization
- Git
- SQL/database integration
- Experience deploying Python/ML solutions in cloud environments is preferred

Coding / Problem Solving Candidates should be comfortable with Python coding problems involving:

- Lists
- Dictionaries
- Sets
- Strings
- Sorting/searching
- Array manipulation
- Data transformation
- Merging datasets/lists
- Basic algorithms and data structures
- Optimization of solutions
- Time and space complexity analysis
- Ability to explain multiple approaches to the same problem

Must-have:

1. Python
2. Classical ML
3. Forecasting
4. Regression & Classification
5. XGBoost/LightGBM/CatBoost
6. ML lifecycle
7. Model evaluation
8. Model monitoring
9. Python coding/DSA
10. Time & Space Complexity

Good-to-have:

- FastAPI/Flask
- Docker
- SQLAlchemy
- REST APIs
- Data quality
- Data drift
- Cloud

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Sr DATA SCIENTIST - Python (Bengaluru)
🏢 Happiest Minds Technologies
📍 Bengaluru