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Key Responsibilities:
- Data Analysis and Interpretation:
Analyze large, complex datasets to extract meaningful insights and trends. Develop and implement statistical models and machine learning algorithms.
- Data Engineering:
Design, build, and maintain scalable data pipelines. Ensure data quality and integrity across various data sources. Optimize data storage and retrieval processes.
- Collaboration:
Work closely with cross-functional teams, including product, engineering, and business teams, to understand data needs and deliver solutions. Communicate findings and recommendations to stakeholders in a clear and concise manner.
- Research and Development:
Stay updated with the latest advancements in data science and data engineering. Experiment with new tools, techniques, and technologies to improve data processes and analytics.
- Deployment and Maintenance:
Deploy data pipelines and machine learning models into production and monitor their performance. Continuously improve and maintain existing data pipelines, data models, and infrastructure.
Qualifications:
Bachelors or Masters degree in Computer Science, Data Science, Statistics, Engineering, or a related field.
Experience:
Minimum of 5 years industry experience in data science, data engineering, or a related field. Proven experience with data analysis, data engineering, data modeling, statistical modeling, and machine learning.
Technical Skills:
- Proficiency in programming languages such as Python, R, or Scala.
- Experience with data processing frameworks like Apache Spark, Hadoop, or similar.
- Strong SQL skills and experience with relational databases.
- Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
- Experience with data visualization tools like Tableau, Power BI, or similar.
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