Automated Detection Researcher - Fraud Analytics (2-7 yrs)

Job Description :

Key Responsibilities :

- Research, design, and develop novel algorithms for automated detection in areas such as fraud, anomalies, security threats, and other relevant domains.

- Conduct in-depth data analysis and feature engineering to extract meaningful insights from large and complex datasets.

- Develop and evaluate machine learning models (e.g., supervised, unsupervised, deep learning) for optimal detection performance.

- Stay abreast of the latest advancements in machine learning, data mining, and related fields.

- Collaborate with cross-functional teams to integrate research findings into real-world applications.

- Publish research findings at conferences and in academic journals (optional).

- Mentor junior researchers and contribute to the growth of the research team.

- Experience with specific detection domains (e.g., financial fraud, network intrusion detection)

- Expertise in specific machine learning techniques (e.g., time series analysis, graph neural networks)

- Experience with cloud computing platforms (AWS, Azure, GCP)

- Strong programming skills in Python and experience with relevant libraries (e.g., scikit-learn, TensorFlow/PyTorch)

Required Skills & Experience :

- 2 - 7 years of experience in research and development within the field of automated detection, machine learning, or a related area.

- Strong understanding of statistical and machine learning concepts, including supervised, unsupervised, and deep learning algorithms.

- Proficiency in Python and experience with common machine learning libraries (scikit-learn, TensorFlow/PyTorch).

- Experience with data analysis and feature engineering techniques.

- Excellent problem-solving, analytical, and critical thinking skills.

- Strong communication and collaboration skills.

- A passion for research and a strong desire to contribute to cutting-edge solutions.

Bonus Points :

- PhD or Master's degree in Computer Science, Statistics, Mathematics, or a related field.

- Experience with specific detection domains (financial fraud, network intrusion detection)

- Expertise in specific machine learning techniques (time series analysis, graph neural networks)

- Experience with cloud computing platforms (AWS, Azure, GCP)

- Publications in top-tier conferences or journals.