Data Science Engineer
Job Overview
The Data Science Engineer is responsible for designing, building, and optimizing data pipelines, machine learning models, and analytics solutions that support data-driven business decisions. This role bridges data engineering and data science, transforming raw data into scalable, production-ready AI and analytics solutions. The ideal candidate can work independently, solve complex data challenges, and collaborate with cross-functional teams.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines and ETL workflows for structured and unstructured data
- Build, train, deploy, and maintain machine learning and AI models in production environments
- Collect, clean, transform, and analyze large datasets to generate actionable insights
- Work closely with business stakeholders, product teams, and engineers to understand data requirements and translate them into technical solutions
- Optimize databases, data warehouses, and data infrastructure for performance, scalability, and reliability
- Ensure data quality, integrity, governance, and security across systems
- Monitor, evaluate, and improve the performance of machine learning models and data workflows
- Create dashboards, reports, and visualizations to support business intelligence and decision-making
- Automate data workflows and improve operational efficiency through scripting and process optimization
- Troubleshoot data issues and provide technical recommendations for process improvements
- Mentor junior team members and contribute to best practices in data engineering and data science
Qualifications
- Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related field
- 3-7 years of professional experience in data science, data engineering, machine learning, or related roles
- Strong hands-on experience in Python and SQL for data processing, analytics, and automation
- Experience working with Oracle DB or other enterprise relational databases
- Solid understanding of machine learning algorithms, statistical analysis, and predictive modeling
- Experience designing and maintaining ETL pipelines and data architectures
- Experience deploying ML models into production environments
- Familiarity with cloud-based data and ML services
- Strong analytical, problem-solving, and debugging skills
- Effective communication skills with the ability to collaborate with technical and non-technical stakeholders
- Ability to work independently, manage multiple priorities, and deliver high-quality solutions.
