
Leading Data Scientist
7 days ago
We are seeking a talented Data Science Engineer to play a pivotal role in designing, implementing, and optimizing 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:
- Design and Implement Scalable Data Pipelines: Design and implement scalable data pipelines to efficiently collect, process, and analyze large volumes of data from various sources.
- Collaborate with Data Scientists: Collaborate with data scientists to transform machine learning models into production-ready applications.
- Optimize and Maintain Data Workflows: Optimize and maintain existing data workflows, ensuring data accuracy, quality, and integrity throughout the process.
- Evaluate New Technologies: Evaluate and integrate new data management and processing technologies to enhance analytics capabilities.
- Create Data Repositories: Create and manage data repositories, following best practices for data governance and security.
- Develop Documentation: Develop documentation and provide training to team members on data systems and workflows.
- Utilize Cloud Platforms: Utilize cloud platforms (e.g., AWS, Azure, Google Cloud) for data storage, processing, and machine learning deployment.
- Stay Updated on Industry Trends: Stay updated on the latest industry trends and technologies in data engineering and machine learning.
- Lead Machine Learning Model Deployment: Lead the development and deployment of machine learning models that drive key business metrics and outcomes.
- Build Scalable Pipelines and Feature Stores: Build and maintain scalable data pipelines and feature stores for training and inference use cases.
- Closely Collaborate with Product Teams: Work closely with product, engineering, and business teams to identify high-impact data science opportunities and close the loop on delivery.
- Maintain Models in Production: Monitor and retrain models in production to ensure performance over time and handle data drift issues.
- Contribute to Architectural Decisions: Contribute to architectural decisions on data platforms and model-serving infrastructure.
- Mentor Junior Team Members: Mentor junior team members and help shape best practices in data science engineering.
Qualifications:
- Bachelor's or Master's degree in Computer Science, Data Engineering, Machine Learning, or a related technical discipline.
- 3-5 years of professional experience in data science and engineering roles, with a track record of delivering production-ready solutions.
- 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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