Tell us where you fit the best, we will tell you how to get there…

We being an employee-centric company, offers you a fun-filled environment to excel in all the tasks you perform. Our endeavors aim to improve your learning curve so that you can gain a significant amount of life-changing knowledge as you work with TOPS. We are looking for the skillful, hardworking and talented individuals who wish to cultivate cross-functional abilities. If you think, you have strong fundamental values and forward thinking approach to stand apart from the crowd – we are here to help you!!!

Data Scientist

Experience: 4+ Years | No of Openings: 1

Job Description

- Own the end-to-end machine learning lifecycle, from problem definition and data exploration to deployment and monitoring.
- Design and develop production-ready machine learning models for geospatial, environmental, and operational prediction problems.
- Build robust feature engineering and data processing pipelines for large-scale datasets.
- Develop and evaluate models using appropriate validation strategies, including spatial and temporal cross-validation where applicable.
- Analyze model performance, identify failure modes, and continuously improve prediction quality.
- Deploy and maintain ML models on AWS infrastructure.




- Collaborate with software engineers to integrate ML services into production applications.
- Recommend appropriate algorithms, tools, and technologies based on business requirements.
- Follow best practices for experimentation, model versioning, documentation, and reproducibility.
- Document model assumptions, limitations, and performance to support explainability and auditability.
- Contribute to building the company's data science practices.

Key Responsibilities

- 4–6 years of hands-on experience in Data Science or Machine Learning.
- Experience designing and deploying production machine learning systems.
- Strong Python programming skills.
- Solid SQL and data analysis skills.
- Solid understanding of machine learning algorithms, feature engineering, model evaluation, and hyperparameter optimization.
- Experience with Scikit-learn, Pandas, NumPy, and modern ML frameworks such as XGBoost, LightGBM, TensorFlow, or PyTorch.
- Experience working with large datasets and production data pipelines.
- Experience deploying ML solutions on AWS using services such as S3, SageMaker, ECS, Lambda, or similar.
- Understanding of software engineering practices including Git, testing, Docker, and CI/CD.
- Ability to solve ambiguous problems and make sound technical decisions.

📌 Data Scientist (India)
🏢 Tops Infosolutions
📍 India