Data Scientist for Innovation

7 days ago

Lahore, Punjab, Pakistan beBee Careers Full time

Data Engineer for Machine Learning

We are seeking a highly skilled Data Engineer to play a pivotal role in designing and implementing data-driven solutions that enhance our machine learning capabilities. The ideal candidate has a strong background in data engineering combined with machine learning and is passionate about applying modern technologies to drive innovation.

  • Key Responsibilities:
  • Data Pipeline Design: Design and implement scalable data pipelines to efficiently collect, process, and analyze large volumes of data from various sources.
  • Collaboration: Collaborate with data scientists to transform machine learning models into production-ready applications.
  • Workflow Optimization: Optimize and maintain existing data workflows, ensuring data accuracy, quality, and integrity throughout the process.
  • Tech Evaluation: Evaluate and integrate new data management and processing technologies to enhance analytics capabilities.
  • Data Repository Management: Create and manage data repositories, following best practices for data governance and security.
  • Documentation and Training: Develop documentation and provide training to team members on data systems and workflows.
  • Cloud Platform Utilization: Utilize cloud platforms (e.g., AWS, Azure, Google Cloud) for data storage, processing, and machine learning deployment.
  • Industry Trends: Stay updated on the latest industry trends and technologies in data engineering and machine learning.
  • Model Deployment: Lead the development and deployment of machine learning models that drive key business metrics and outcomes.
  • Pipeline Scalability: Build and maintain scalable data pipelines and feature stores for training and inference use cases.
  • Collaboration with Cross-Functional Teams: Work closely with product, engineering, and business teams to identify high-impact data science opportunities and close the loop on delivery.
  • Model Monitoring: Monitor and retrain models in production to ensure performance over time and handle data drift issues.
  • Architectural Decisions: Contribute to architectural decisions on data platforms and model-serving infrastructure.
  • Mentorship: Mentor junior team members and help shape best practices in data science engineering.

Requirements

  • Education: Bachelor's or Master's degree in Computer Science, Data Engineering, Machine Learning, or a related technical discipline.
  • Experience: 3-5 years of professional experience in data science and engineering roles, with a track record of delivering production-ready solutions.
  • Candidate Qualifications: Demonstrated experience translating business problems into data science projects with measurable outcomes. Prior experience working closely with business stakeholders to operationalize models and drive ROI.
  • Soft Skills: Strong analytical and problem-solving skills with attention to detail. Excellent communication skills, both verbal and written, to convey technical concepts effectively. Ability to work collaboratively in a fast-paced team environment and manage multiple priorities. Motivated self-starter with a passion for learning and applying new technologies.

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