As a Data Scientist, you will own the entire lifecycle of our machine learning models, from initial concept and data exploration to production deployment.

This role requires a strong blend of statistical knowledge, coding expertise, and the ability to translate complex analytical findings into clear business recommendations.

Key Responsibilities :

- Lead the research, design, and implementation of cutting-edge Machine Learning models (e.g., Deep Learning, NLP, Recommendation Systems) to solve critical business problems.

- Develop robust, efficient, and scalable ETL/data pipelines using Python and SQL to prepare large, raw datasets.

- Implement MLOps principles to ensure repeatable, reliable, and automated model deployment and monitoring, ideally using tools like AWS SageMaker or Kubeflow.

- Perform rigorous statistical analysis and A/B testing to validate model performance and measure the impact of features.

- Collaborate with engineering and product teams to integrate models into production applications.

Technical Skills Required :

- 4+ years of experience in a Data Scientist or ML Engineering role.

- Expertise in Python with essential libraries: Pandas, NumPy, Scikit-learn, and TensorFlow/PyTorch.

- Advanced proficiency in SQL for complex data manipulation.

- Demonstrated experience with cloud computing environments (AWS, Azure, or GCP).

- Strong foundation in Statistics, Probability, and Experimental Design.

- Familiarity with Big Data technologies like Spark is a plus