Description

Responsibilities:

• Develop and implement data models and algorithms to analyze large datasets.
• Collaborate with cross-functional teams to understand data requirements and deliver data-driven solutions.
• Design and maintain scalable data pipelines and architectures to support data processing and analysis.
• Utilize statistical methods to analyze data and generate useful business insights.
• Communicate findings and insights to stakeholders through data visualization and reporting.
• Continuously improve data collection and processing techniques to enhance data quality and efficiency.
• Stay updated with the latest industry trends and technologies in data science and engineering.

Mandatory Skills:

• Proven experience in Data Engineering, including data pipeline development and ETL processes.
• Strong proficiency in programming languages such as Python, R, or Scala.
• Expertise in SQL and database management systems (e.g., PostgreSQL, MySQL, or NoSQL databases).
• Experience with data visualization tools (e.g., Tableau, Power BI, or similar).
• Solid understanding of machine learning algorithms and statistical modeling techniques.
• Familiarity with cloud platforms (e.g., AWS, Azure, or Google Cloud) for data storage and processing.

Preferred Skills:

• Experience with big data technologies (e.g., Hadoop, Spark).
• Knowledge of data governance and data quality frameworks.
• Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).
• Experience in deploying machine learning models in production environments.
• Strong problem-solving skills and ability to work in a fast-paced environment.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.
• 7-10 years of relevant experience in data science and data engineering roles.
• Strong analytical and critical thinking skills.
• Excellent communication and collaboration skills

Key Skills

Education

Bachelor's or Master's degrees