Description

About Trudenty:

Trudenty is an early-stage startup building a consumer data network for trusted commerce. Trudenty enables the commerce ecosystem to share intelligence about fraud trends and fraudster profiles operating across the ecosystem. The Trudenty Trust Network helps merchants personalise consumer experiences (to improve consumer experience, loyalty and retention) based on fraud risk and prevent fraud.

We are looking for a Machine Learning Engineer with an aptitude for data science and a track record of implementing fraud prevention, scoring or personalisation algorithms. As a key member of our technical team, you will play a crucial role in advancing our machine learning capabilities.

Responsibilities:

• **Algorithm Development:**

- Design, develop and implement advanced machine learning algorithms for fraud prevention and user personalisation.

• **Model Training and Optimisation:**

- Train and fine-tune machine learning models using relevant datasets to achieve optimal performance.

- Implement strategies for continuous model improvement and optimisation.

• **Data Analysis:**

- Analyse and preprocess large datasets to extract meaningful insights and features for model training.

• **Collaboration:**

- Collaborate with cross-functional teams, including data scientists, engineers, and product managers, to understand business requirements and implement effective solutions.

• **Research and Innovation:**

- Stay abreast of the latest advancements in machine learning and contribute to the exploration and integration of innovative techniques.

• **Code Review and Documentation:**

- Conduct code reviews to ensure high-quality, scalable, and maintainable code.

- Create comprehensive documentation for developed algorithms and models.

• **Deployment into production environments, Monitoring and Maintenance:**

Manage the deployment of models into production

- Implement monitoring solutions to track the performance of deployed models and proactively address any issues that may arise.

Requirements

• A degree in Computer Science, Machine Learning, or a related field
• Experience with Fraud Detection algorithms, approaches, and model tuning
• Strong proficiency in Python software development
• General experience with AI tools and technologies, especially in developing Fraud Detection Systems
• Familiarity with open source AI libraries and frameworks (TensorFlow, PyTorch and scikit-learn)
• Solid understanding of machine learning concepts and techniques
• Strong problem-solving skills and the ability to work independently and as part of a team,
• Experience with programming in NodeJS, JS,TS are a plus

Benefits

• Stock options/equity: Generous equity as a member of our founding team
• Pension plan: to help you start saving for you future
• Flexible work arrangements: Hybrid work environment - mostly remote with 1-2 days in office weekly
• Learning and development: Professional development through professional coaching and access to online courses (for functional skills)