Responsibilities

• Analyze large datasets to extract actionable insights and support data-driven decision-making processes.
• Develop and implement machine learning models to solve complex business problems.
• Collaborate with cross-functional teams to understand business requirements and translate them into data solutions.
• Perform data preprocessing cleaning and transformation to ensure data quality and integrity.
• Create and maintain data pipelines to automate data collection and processing tasks.
• Utilize Python to develop and deploy data analysis and machine learning algorithms.
• Visualize data using tools like Matplotlib Seaborn or similar to communicate findings effectively.
• Conduct exploratory data analysis to identify trends patterns and anomalies in the data.
• Provide technical support and guidance to team members on data-related tasks and projects.
• Document methodologies processes and findings to ensure reproducibility and knowledge sharing.
• Stay updated with the latest advancements in data science and machine learning to continuously improve skills and knowledge.
• Participate in code reviews and contribute to the development of best practices for data science projects.
• Ensure compliance with data privacy and security regulations in all data-related activities.

Qualifications

• Possess a Bachelors or Masters degree in Data Science Computer Science Statistics or a related field.
• Have 3 to 5 years of hands-on experience in data science and machine learning.
• Demonstrate proficiency in Python for data analysis and machine learning tasks.
• Show experience with data visualization tools like Matplotlib Seaborn or similar.
• Exhibit strong problem-solving skills and the ability to work with large datasets.
• Have excellent communication skills to effectively collaborate with cross-functional teams.
• Display knowledge of data preprocessing cleaning and transformation techniques.
• Understand the principles of machine learning and statistical analysis.
• Be familiar with data privacy and security regulations.
• Show a proactive approach to learning and staying updated with industry trends.
• Demonstrate the ability to document and share methodologies and findings.
• Have experience with version control systems like Git.
• Be able to work in a hybrid model with day shifts.

Certifications Required

Certified Data Scientist (CDS) Python for Data Science Certification

The Cognizant community:
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