Experience
5 - 10 yrs
Job Location
India
Vacancy
1
Designation
Data Scientist
Job Type
Not specified
Job Description
Data Scientist Job Description
Company: Codvo
Job Title: Data Scientist
Experience: 4+ years
About the Role
We are seeking a highly skilled Data Scientist with a strong background in Machine Learning and Deep Learning to join our team. The ideal candidate will have experience applying advanced ML techniques to solve real-world business and customer problems, and will be comfortable working with large, complex datasets.
Key Responsibilities
Design and implement end-to-end ML pipelines, including data ingestion, cleaning, feature engineering, model training, deployment, and monitoring.
Develop and experiment with Deep Neural Network architectures for various business use cases.
Translate ambiguous business requirements into clear technical solutions and communicate insights effectively to both technical and non-technical stakeholders.
Work with large datasets for acquisition, preprocessing, and analysis.
Ensure code quality and maintainability by following software engineering best practices.
Collaborate with cross-functional teams to integrate ML solutions into production systems.
Utilize CI/CD, version control (Git), and automated testing in ML projects.
Required Skills Qualifications
5+ years of experience applying Machine Learning to real-world business/customer problems.
Strong programming skills in Python and experience with ML libraries such as scikit-learn, pandas, numpy, TensorFlow, PyTorch, and Keras.
Solid foundations in Deep Learning with hands-on experience in designing and deploying neural network architectures.
Experience building robust ML pipelines and deploying models in production environments.
Strong understanding of software engineering principles for maintainable and testable codebases.
Ability to communicate technical concepts clearly to diverse audiences.
Experience with CI/CD, Git, and automated testing in ML workflows.
Nice to Have
Exposure to cloud platforms (AWS, GCP, Azure) for ML deployment.
Familiarity with MLOps tools and frameworks.