Senior Data Scientist/Engineer
1 month ago
Data Analysis and Interpretation:
- Analyze and interpret complex datasets to uncover trends, patterns, and actionable insights.
- Develop and implement advanced statistical models and machine learning algorithms to solve business problems.
Data Engineering:
- Design, develop, and maintain scalable data pipelines and architectures.
- Ensure data quality, integrity, and security across various sources.
- Optimize data storage solutions for efficiency and performance.
Project Leadership:
- Lead data science and engineering projects from conception to deployment.
- Coordinate with cross-functional teams, including product, engineering, and business stakeholders, to ensure successful project delivery.
- Define project scope, goals, and deliverables that support business objectives.
Mentorship and Collaboration:
- Mentor and provide guidance to junior data scientists and engineers.
- Foster a collaborative and innovative team environment.
- Communicate complex technical concepts and insights to non-technical stakeholders.
Research and Development:
- Stay current with the latest advancements in data science, engineering, and machine learning.
- Experiment with new tools, techniques, and technologies to continuously improve data processes and analytics.
Deployment and Maintenance:
- Deploy and monitor machine learning models in production environments.
- Continuously improve and maintain existing data models and infrastructure.
- Implement best practices for model management and version control.
Qualifications:
- Masters or Ph.D. degree in Computer Science, Data Science, Statistics, Engineering, or a related field.
Experience:
- 5+ years of experience in data science, data engineering, or a related field.
- Proven experience leading data projects and managing teams.
- Extensive experience with data analysis, statistical modeling, and machine learning.
Technical Skills:
- Proficiency in programming languages such as Python, R, or Scala.
- Expertise in data processing frameworks like Apache Spark, Hadoop, or similar.
- Strong SQL skills and experience with relational and NoSQL databases.
- Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
Advanced knowledge of data visualization tools like Tableau, Power BI, or similar.
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