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.