Summary
Overview
Work History
Education
Skills
Languages
Accomplishments
References
Timeline
Generic

Júlia Potratz

Dublin

Summary

Dynamic Trust & Safety Specialist and Developer Programmer with a proven track record at Whatnot and Pontifical Catholic University of Rio de Janeiro. Expert in Python and deep learning algorithms, I excel in crisis management and data analysis, significantly enhancing marketplace safety and operational efficiency through innovative solutions and empathetic, cross-functional communication and multi skills.

Overview

6
6
years of professional experience

Work History

Trust Snd Safety Specialis

Whatnot
Dublin
10.2021 - Current

Work as the front-line support, assisting customers with highly escalated & emergency issues related to the Whatnot platform. Provide expert inbound email and chat-based customer service for users in crisis.My role centers around de-escalating challenging situations and delivering clear, informative guidance that fosters resolution, and enhances the safety of the marketplace. and resolve high-complexity cases, ensuring customer satisfaction while maintaining a focus on sensitive, high-stakes issues. In this role, I combine strong communication skills, empathy, and problem-solving abilities to effectively resolve issues and contribute to a safer, more supportive marketplace environment.

  • Inbound Support & Crisis Management: Deliver compassionate, clear communication to users in distress via email and chat, de-escalating difficult situations and guiding users toward resolution.
  • Trust & Safety Case Investigation: Thoughtfully investigate cases with high complexity, focusing on high-sensitivity issues while ensuring timely and accurate resolutions.
  • Collaboration Across Departments: Work with internal teams to gather information, research open questions, and resolve customer concerns, ensuring a smooth and cohesive service experience.
  • Backlog Management & Performance Monitoring: Efficiently manage and resolve a backlog of open issues, tracking key performance metrics to identify and implement improvements in service delivery.
  • Data-Driven Insights: Review and analyze performance data to make informed, proactive decisions that optimize internal processes, improve customer satisfaction, and redue finaltial risk for the company.
  • Professional Representation: Represent the company with integrity and professionalism, ensuring every interaction reflects our commitment to safety and quality service.
  • Training and Quality assurance: Create and drive knowledge development process for new specialists, focusing on skills and competencies of employees or individuals to perform their tasks effectively and efficiently. Evaluating performance and ensuring that the training programs are effective, up-to-date, and deliver the desired results.

Developer Programmer

Pontifical Catholic University of Rio de Janeiro
Rio De Janeiro
08.2018 - 03.2022

Program developer using computational intelligence and machine learning tools, focusing mainly on Deep Learning algorithms. Specialist in software development, using the Python language and also as a backend and frontend developer using Python, SQL, Flask, CSS and HTM. The main objectives of the projects I've worked on revolve around data analysis and the development of intelligent tools that can help solve complex and time-consuming problems, in order to find solutions that are close to the real world.

  • Evaluated various libraries and frameworks to identify best solutions for specific requirements.
  • Designed and implemented unit and integration tests in Python to ensure software quality.
  • Monitored equipment function to verify conformance with specifications.
  • Recommended improvements to facilitate team and project workflow.
  • Utilized Python libraries such as NumPy and Pandas for data analysis and manipulation tasks.
  • Analyzed code and corrected errors to optimize output.
  • Developed Python scripts to automate data processing tasks.

Education

Bachelor of Science - Electrical Engineering

State University of Rio De Janeiro
Rio De Janeiro, Brasil
12-2019

Master of Science - Decision Support Methods

Pontifical Catholic University of Rio De Janeiro
Rio De Janeiro

Skills

  • Python
  • Natural language processing
  • Deep learning algorithms
  • Data preprocessing
  • Operational efficiency
  • Cross-functional, clear and concise communication
  • Emotional intelligence
  • Risk Assessment
  • Data Analysis
  • Problem Solving
  • Attention to Detail
  • Content Moderation
  • Security & Privacy Regulations, Compliance Requirements and Understanding of Legal Implications
  • Enforcement Techniques
  • Customer Support and Incident Response
  • Conflict Resolution, Bias Mitigation
  • Empathy and Diplomacy
  • Cybersecurity Awareness
  • Global Perspective
  • Sensitivity to Sensitive Content
  • Ethical Decision-Making
  • Documentation and Reporting
  • Rapid Response
  • Decision-Making Under Pressure
  • Strong Stakeholder Collaboration
  • Staying Up-to-Date
  • Flexibility
  • Learning from Feedback
  • Time Management
  • Process Improvement
  • Team Collaboration
  • Multilingual Capabilities
  • User Education

Languages

Portuguese
First Language
English
Advanced (C1)
C1

Accomplishments

Papers published in event proceedings (complete)

  • POTRATZ, JULIA; CANCHUMUNI, SMITH W.A.; CASTRO, JOSE DAVID BERMUDEZ; EMERICK, ALEXANDRE A.; PACHECO, MARCO AURELIO C.
    Large Dimension Parameterization with Convolutional Variational Autoencoder: An Application in the History Matching of Channelized Geological Facies Models In: 2020 20th International Conference on Computational Science and Its Applications (ICCSA), 2020, Cagliari.
    2020 20th International Conference on Computational Science and Its Applications (ICCSA). IEEE, 2020. p.23 - Additional references: Brazil/Portuguese. Home page: http://https://ieeexplore.ieee.org/document/9257505

Magazine articles

  • CANCHUMUNI, SMITH W.A.; CASTRO, JOSE DAVID BERMUDEZ; POTRATZ, JULIA; PACHECO, MARCO AURELIO C.; EMERICK, ALEXANDRE A.
    Recent developments combining ensemble smoothing and deep generative networks for facies history matching. Computational Geosciences. Computational Geosciences, p.1499 - 1573, 2020. Additional references: Brazil/English. Media: Digital media. Home page: https://link.springer.com/article/10.1007/s10596-020-10015-0

References

References available upon request.

Timeline

Trust Snd Safety Specialis

Whatnot
10.2021 - Current

Developer Programmer

Pontifical Catholic University of Rio de Janeiro
08.2018 - 03.2022

Bachelor of Science - Electrical Engineering

State University of Rio De Janeiro

Master of Science - Decision Support Methods

Pontifical Catholic University of Rio De Janeiro
Júlia Potratz