Job Title: Data Scientist
Job Location: Bangalore
Experience: 4-5 Years
About the Role:
We are looking for experienced Data Scientist. The candidate should have expertise in building machine learning and econometrics models, proficiency in Python and PySpark, and experience working with AWS cloud infrastructure, including SageMaker. The role will also require a working knowledge of MLOps practices, client management, and collaboration with cross-functional teams. While forecasting expertise is a valuable skill, it will be a secondary focus in this position.
Key Responsibilities:
- Design, develop, and deploy machine learning and statistical models to solve complex business problems.
- Collaborate with cross-functional teams (data engineering, ML engineering, and business) to gather and understand requirements.
- Implement and scale machine learning models using Python and PySpark, optimising performance and accuracy.
- Utilize AWS services (including SageMaker) for deploying, training, and managing models in the cloud.
- Apply MLOps best practices to ensure scalability, reliability, and maintainability of ML pipelines.
- Develop and implement forecasting models as needed, but primary focus will be on other types of machine learning and statistical time series models.
- Work closely with business stakeholders to translate business needs into technical solutions.
Required Skills & Experience:
- 4-5 years of experience in data science, with a strong focus on machine learning and statistical model development.
- Proficiency in Python and PySpark for large-scale data processing and modelling.
- Hands-on experience with AWS cloud services, especially SageMaker for building and deploying models.
- Familiarity with MLOps tools and best practices for managing machine learning pipelines.
- Demonstrated ability to develop accurate forecasting models (though this will be a secondary skill).
- Strong communication skills with the ability to manage client relationships and expectations effectively.
- Experience working in collaborative, cross-functional teams, including engineers, product managers, and business stakeholders.
Preferred Qualifications:
- Experience with big data tools like Spark.
- Exposure to advanced machine learning techniques (e.g., deep learning, reinforcement learning).
- Familiarity with CI/CD pipelines for machine learning.
