Junior Data Scientist - Fraud Detection

Role Overview

As a Junior Data Scientist specializing in fraud detection, you will be instrumental in developing and implementing machine learning models to identify and prevent fraudulent activities. You will collaborate with senior data scientists and engineers, contributing to the improvement of fraud detection capabilities and ensuring data integrity. Your responsibilities will include collecting, cleaning, and analyzing large datasets to identify patterns and anomalies indicative of fraud, using statistical techniques and machine learning algorithms to build predictive models, testing and validating models, documenting findings, presenting them to stakeholders, monitoring model performance, and staying up-to-date with fraud detection trends.

Key Responsibilities

• Develop and implement machine learning models for fraud detection.
• Collect, clean, and preprocess large datasets for analysis.
• Perform statistical analysis and data mining to identify fraudulent patterns.
• Test and validate models to ensure accuracy and reliability.
• Collaborate with senior data scientists and engineers to improve model performance.
• Document findings and present them to stakeholders.
• Monitor model performance and make necessary adjustments.
• Stay up-to-date with the latest trends and techniques in fraud detection.
• Contribute to the development of data governance policies.
• Participate in code reviews and contribute to the development of best practices.

Qualification Required

• Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field. Master's degree preferred.
• Proficiency in Python or R, including experience with relevant libraries such as scikit-learn, TensorFlow, or Keras.
• Experience with SQL and database management systems (e.g., MySQL, PostgreSQL).
• Familiarity with data visualization tools such as Tableau or Power BI.
• Strong understanding of statistical analysis and machine learning techniques.
• Excellent problem-solving and analytical skills.
• Ability to work independently and as part of a team.
• Strong communication and presentation skills.
• Knowledge of fraud detection techniques and best practices is a plus.
• Experience with big data technologies such as Hadoop or Spark is a plus.

Benefits Included

• Comprehensive health insurance coverage, including medical, dental, and vision.
• Generous paid time off, including vacation, sick leave, and holidays.
• Professional development opportunities, including training courses and conferences.
• Employee assistance program providing confidential counseling and support services.
• Retirement savings plan with company match to help you save for the future.
• Life insurance and disability coverage to protect you and your family.
• Performance-based bonuses to reward your hard work and contributions.
• Employee discounts on company products and services.
• Wellness programs to promote a healthy lifestyle.

Role Overview

As a Junior Data Scientist specializing in fraud detection, you will be instrumental in developing and implementing machine learning models to identify and prevent fraudulent activities. You will collaborate with senior data scientists and engineers, contributing to the improvement of fraud detection capabilities and ensuring data integrity. Your responsibilities will include collecting, cleaning, and analyzing large datasets to identify patterns and anomalies indicative of fraud, using statistical techniques and machine learning algorithms to build predictive models, testing and validating models, documenting findings, presenting them to stakeholders, monitoring model performance, and staying up-to-date with fraud detection trends.

Key Responsibilities

• Develop and implement machine learning models for fraud detection.
• Collect, clean, and preprocess large datasets for analysis.
• Perform statistical analysis and data mining to identify fraudulent patterns.
• Test and validate models to ensure accuracy and reliability.
• Collaborate with senior data scientists and engineers to improve model performance.
• Document findings and present them to stakeholders.
• Monitor model performance and make necessary adjustments.
• Stay up-to-date with the latest trends and techniques in fraud detection.
• Contribute to the development of data governance policies.
• Participate in code reviews and contribute to the development of best practices.

Qualification Required

• Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field. Master's degree preferred.
• Proficiency in Python or R, including experience with relevant libraries such as scikit-learn, TensorFlow, or Keras.
• Experience with SQL and database management systems (e.g., MySQL, PostgreSQL).
• Familiarity with data visualization tools such as Tableau or Power BI.
• Strong understanding of statistical analysis and machine learning techniques.
• Excellent problem-solving and analytical skills.
• Ability to work independently and as p