Description : About the Role :
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(ref : hirist.tech)