About the job
Devsinc is on the lookout for a skilled Senior Software Engineer specializing in Data Science to join our innovative team. In this critical role, you will design, implement, and optimize data-driven solutions that enhance our machine learning capabilities. The ideal candidate possesses a robust background in data engineering and machine learning and has a passion for leveraging modern technologies to foster innovation. You will work collaboratively with data scientists, analysts, and software engineers to build powerful data pipelines and deploy cutting-edge models.
Key Responsibilities:
- Design and implement scalable data pipelines to effectively collect, process, and analyze large data sets from diverse sources.
- Collaborate with data scientists to convert machine learning models into deployable applications.
- Optimize and maintain current data workflows, ensuring accuracy, quality, and integrity throughout.
- Assess and integrate emerging data management and processing technologies to boost analytics capabilities.
- Create and manage data repositories while adhering to best practices for data governance and security.
- Develop documentation and provide training to team members on data systems and workflows.
- Utilize cloud platforms (e.g., AWS, Azure, Google Cloud) for data storage, processing, and machine learning deployment.
- Stay updated on the latest industry trends and technologies in data engineering and machine learning.
- Lead the development and deployment of machine learning models that influence key business metrics.
- Build and maintain scalable data pipelines and feature stores for training and inference applications.
- Engage closely with product, engineering, and business teams to identify impactful data science opportunities and ensure successful delivery.
- Monitor and retrain production models to maintain performance and address data drift issues.
- Contribute to architectural decisions regarding data platforms and model-serving infrastructure.
- Mentor junior team members and help establish best practices in data science engineering.