Machine Learning Engineer - Freelance

Job Title: Freelance Machine Learning Engineer

Location: Germany (Remote/On-Site Flexibility)

Industry: Financial Services

Duration: Project-Based (3-6 months, with potential extension)

Responsibilities

• Fraud Detection and Prevention:
• Develop and implement ML models to identify and prevent fraudulent activities, such as unauthorized transactions and identity theft.
• Utilise anomaly detection techniques (e.g., unsupervised learning) to identify unusual patterns in data.
• Train supervised learning models on labelled fraud datasets to improve accuracy and precision in fraud identification.
• Implement real-time fraud monitoring systems using reinforcement learning or similar approaches.
• Collaborate with cross-functional teams, including data analysts, engineers, and compliance officers, to align solutions with business needs and regulatory requirements.
• Build and optimise scalable pipelines for fraud detection in real-time environments.
• Ensure all models comply with data privacy laws (e.g., GDPR) and adhere to the highest standards of security.
• Conduct ongoing research on the latest ML techniques for fraud prevention and integrate new methodologies into existing systems.
• Document processes, models, and findings, and provide knowledge transfer to internal teams.

Qualifications

Technical Skills:

• Strong programming skills in Python and expertise in ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Proven experience in anomaly detection, supervised learning, and reinforcement learning techniques.
• Hands-on experience with real-time monitoring systems and building scalable data pipelines.
• Familiarity with financial datasets and understanding of challenges in fraud detection within the financial services industry.
• Proficiency in using SQL and data processing tools for feature engineering and analysis.