```html 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. ```#J-18808-Ljbffr