Data Scientist / Machine Learning Engineer - Python

About the Opportunity :

We are seeking a passionate and technically proficient Data Scientist / Machine Learning Engineer to design, build, and deploy intelligent, data-driven solutions that power predictive analytics, automation, and decision-making systems.

The ideal candidate will have strong experience in Python / R, machine learning frameworks (TensorFlow, PyTorch, Scikit-learn), and feature engineering, along with a solid grasp of data pipeline development and model deployment on cloud platforms.

This role combines applied data science with production-grade ML engineering bridging the gap between algorithm development and real-world implementation.

Key Responsibilities :

• Design and implement machine learning models, including regression, classification, clustering, and time-series forecasting.
• Develop and maintain data pipelines for model training, validation, and deployment.
• Perform feature engineering, data cleaning, and transformation on structured and unstructured datasets.
• Work with large-scale datasets using SQL, Pandas, and Spark to enable high-performance model training.
• Collaborate with product and engineering teams to integrate ML models into production systems.
• Optimize model performance using techniques such as hyperparameter tuning, cross-validation, and regularization.
• Utilize deep learning frameworks (TensorFlow, PyTorch) for advanced use cases such as NLP, computer vision, or anomaly detection.
• Implement end-to-end MLOps pipelines for model monitoring, versioning, and retraining.
• Use cloud-based ML platforms (AWS Sagemaker, Azure ML, or GCP Vertex AI) for scalable experimentation and deployment.
• Communicate analytical findings and insights to technical and non-technical stakeholders through clear visualizations and reports.

Required Skills and Qualifications :

Preferred Skills :

(ref : hirist.tech)