Data Scientist

Job Descriptions:

• Gather, clean, and preprocess large datasets from various sources, ensuring data quality and integrity.
• Develop automated processes for data collection and cleaning to streamline workflows.
• Conduct thorough exploratory analysis to identify patterns, trends, and anomalies in the data.
• Visualize insights using tools such as matplotlib, seaborn, or Tableau to facilitate understanding and decision-making.
• Apply statistical techniques and machine learning algorithms to build predictive models and solve business problems.
• Collaborate with cross-functional teams to define modeling objectives and translate them into actionable insights.
• Engineer features and select relevant variables to improve model performance and generalization.
• Optimize models through hyperparameter tuning, cross-validation, and ensemble methods.
• Evaluate model performance using appropriate metrics and validation techniques.
• Deploy models into production environments, integrating them with existing systems and monitoring their performance over time.
• Communicate findings and recommendations to stakeholders in clear, non-technical language, fostering collaboration and understanding.
• Collaborate with data engineers, software developers, and business analysts to drive data-driven decision-making across the organization.

Requirements:

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field.
• Strong proficiency in programming languages such as Python, with experience using libraries like pandas, numpy, scikit-learn, or TensorFlow.
• Solid understanding of statistical concepts and machine learning techniques, with hands-on experience in model development and evaluation.
• Experience deploying data science solutions in production-level environments, ensuring scalability, reliability, and performance.
• Excellent communication skills and ability to collaborate effectively in a cross-functional team environment.