Description

You will build machine learning and deep learning solutions for identity risk, account takeover, and payment fraud detection.

Responsibilities

• Perform hands-on data exploration, processing, and analysis on massive datasets.
• Apply machine learning, deep learning, and reinforcement learning techniques to build fraud and risk assessment solutions.
• Research and develop advanced algorithms to solve complex business problems.
• Communicate project results to stakeholders and present findings at internal or external conferences.
• Contribute to core machine learning capabilities using deep knowledge of ML and software engineering.

Required Skills

• Proficiency in Python, TensorFlow, and Keras.
• Strong background in machine learning, deep learning, and statistical analysis.
• Experience working with large datasets and cloud computing (Hive, Spark, GCP, or Azure).
• Proficiency in SQL, Python, Java, or JavaScript.
• Experience with software development and machine learning engineering.
• Advanced degree (Master or PhD) in a STEM field with 4-6 years of experience, or a Bachelor's degree in a quantitative field with 3+ years of experience.
• Knowledge of implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards.

Preferred Skills

• Successful completion of assessments in Python, Spark, Scala, or R.
• Experience with open source frameworks such as scikit-learn or PyTorch.
• Background in optimization models or econometrics.

Key Skills

Education

Bachelor's degree