Working Student at Fraunhofer Institute focusing on Data Science and Natural Language Processing. Involved in AI - driven projects with a flexible work schedule.
About the role
- Data Scientist leading the development and deployment of advanced ML models for fraud prevention at Topaz, focusing on innovative and reliable financial solutions.
Responsibilities
- At Topaz, you will be responsible for leading the development and deployment of advanced models that drive large-scale fraud prevention.
- Design, train, and validate machine learning models using advanced algorithms.
- Conduct experiments to test new approaches, tune hyperparameters, and evaluate metrics such as FPR and recall.
- Collaborate with MLOps engineers to build robust pipelines that ensure model scalability in production environments.
- Monitor model performance in production, identifying potential degradation or opportunities for continuous improvement.
- Update models with new data to ensure they remain relevant in the face of changing fraudulent behavior.
- Implement explainability techniques to make models transparent and aligned with applicable regulations.
- Explore new technologies, frameworks, and algorithms to keep the solution at the forefront of fraud detection.
- Contribute to the establishment of best practices and technical standards within the team.
Requirements
- Experience in machine learning, data science, or software development focused on ML-based solutions.
- Hands-on experience developing and deploying advanced models, including supervised, unsupervised learning, and deep learning.
- Experience leading technical projects or multidisciplinary teams. To join our team, we are looking for professionals with solid experience and strong technical knowledge in data engineering.
Benefits
- Health and wellbeing: Because we care about our teams, we offer various health plans focused on promoting wellbeing within the organization.
- Personal and professional development: We are constantly evolving. For this reason, we provide environments, programs, and policies that ensure the space and opportunities you need 🎓 Career path.
- Flexibility and time off: Here you'll find the time needed to recharge, and you can enjoy a day off on your birthday 🥳 Hybrid work arrangement.
- Corporate partnerships and discounts: We offer a range of partner programs and employee discounts.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Location requirements
Werkstudent*in in Data Science und Natural Language Processing bei Fraunhofer, tätig in KI - gestütztem Wissensmanagement und innovativer KI - Lösungsentwicklung.
Data Science Internship at Engineering focused on empowering digital transformation. Join a team that values innovative solutions and professional growth in IT.
Business Analyst acting as a critical link between business and technical teams at Vodafone. Involves gathering requirements and ensuring technical specifications in telecom projects.
Data Scientist developing statistical models and rules for Allegro's eCommerce platform. Driving insights and collaborating across teams to improve product catalog and selection.
Data Scientist developing statistical models and improving product quality for Allegro's eCommerce platform. Collaborating with cross - functional teams to deliver insights and drive business solutions.
Data Scientist at Imprint leveraging data analytics to enhance co - branded credit card offerings and optimize financial product decisions. Collaborating with cross - functional teams in a high - impact role.
Senior Data Scientist leveraging advanced analytical techniques to support Walmart's strategic objectives. Collaborating across functions, mentoring team members, and ensuring data governance standards.
Principal Data Scientist formulating strategies for AI/ML deployment in production at Walmart Global Tech. Leading projects involving state - of - the - art LLMs and collaborating with cross - functional teams.
Senior Clinical Data Manager providing project support and oversight for clinical data management at AstraZeneca. Ensuring data quality and regulatory compliance in clinical studies.