Unlocking the Value of Data and Artificial Intelligence.

NN, CNN, Transfer Learning, LSTM, AE, GAN, Transformers - TensorFlow and PyTorch as frameworks

git, docker, AWS, Python 3.7+, Pandas, Numpy, Matplotlib, Seaborn, Sckit-Learn, W&B, quantization, pruning, FastAPI

• Luciana Maschi Thesis: "Clasificación de Interacciones para la identificación de motivos de contacto" - Topic Modeling• Gonzalo Mordecki Thesis: "The Medium is the Message"Applying Machine Learning for Communications at Resolve, a Digital Debt Collection SaaS.

Zenpli helps companies in LatAm grow by preventing identity fraud and ensuring regulatory compliance without hassle.

Tech >> Process >> HumansAs a Manager i'm responsible for preventing, detecting and investigating fraud across all albo.This position will interact with all levels in the company including senior leadership and C-Level, reporting directly to the CTO.I work with other departments to develop anti-fraud policies and procedures, we use Machine Learning / Deep Learning models & Data Analytics to identify patterns of fraud. I also train employees on how to recognize and report fraud, and I investigate suspicious activity.Some of my task are: • Developing and implementing fraud prevention strategies.• Designing and managing fraud detection systems. (System's using Golang to perform in real-time under 100ms)• Analyzing data to identify trends / patterns in fraud. (Neo4j & Graph Data Science to detect Fraud Rings and track end to end transaction)• Implement ML/DL algorithms into services and pipelines to be consumed via API's (using Python, PyTorch, PySpark).• Design, develop and maintain machine learning solutions in a Live environment (GCP Vertex AI , AWS Sagemaker) to predict and detect fraud. • Investigating cases of suspected fraud. (Strong skills in Analyitics and Forensics, with a lot of expiriences in the business)• Working with Risk & Compliance and Legal team to prosecute cases of fraud.

• As a Lead, i am responsible for mentoring team members, drive and define strategy and monitoring progress towards goals.• This position will interact with all levels in the company including senior leadership and C-Suite.• Design, develop and maintain machine learning solutions in a Live environment (GCP Vertex AI , AWS Sagemaker). • Build, validate, and iterate on models to optimize based on stakeholder goals.• Identify, find, utilize and create relevant data in relational and non-relational databases.• Create and utilize data pipelines and distributed computing architecture.• Effectively communicate with various cohorts with varied technical expertise, meet with internal and external stakeholders to define requirements and goals.• Propose new machine learning techniques and opportunity areas based on cutting edge research.• Drives leading-edge projects/initiatives that impact critical directions of the organization.• Through personal effort, support attainment of multiple short- and mid-term objectives of the organization.

• Lead the end-to-end architecture and development of machine learning solutions for dlocal.• Implement machine learning algorithms into services and pipelines to be consumed at web-scale.• Work with Data Scientist team to deeply understand their business and technical needs and design ML solutions that make the best use of the Cloud platform and ML Frameworks / Services.• Act as a technical liaison between product team and the service engineering teams to provide product enhancement feedback.• Capture and share best-practice knowledge amongst the dlocal architect community.• Build deep relationships with senior technical individuals within product team to enable them to be cloud advocates• Thought Leadership – Evangelize ML Services and share best practices through forums such as blogs, white-papers, reference architectures and public-speaking events, etc.

• Machine learning models applied to fraud prevention, using Scikit-learn, Pyspark, A/B Testing. • CI / CD with SageMaker Pipelines, Apache Airflow and Feature Store • Participation in the creation of a datalake in AWS • Streaming and batch Data Architecture• Developer fuzzy search algorithms to quickly map data in a real-time evaluation.• Presentation model results.• Data Engineer tasks with AWS tools such as S3 buckets, Lambdas, Crawlers and Glue, as well as Spark clusters using CloudFormation

• Machine learning models and data engineer tasks for different retailers in USA • Amazon Web Services as infrastructure.• Unsupervised learning techniques to detect business opportunities.

• Analysis and visualization of transactional data from financial entities.• Predictive models using Supervised Learning techniques to fraud prevention

• API Rest developer for different integrations with external services• Working with different Acquiers and Issuers, surveying functionalities for their business logic.* Banco Sicredi (Porto Alegre - Brasil) * Banco Banestes (Espírito Santo - Brasil) * Carrefour (São Paulo - Brasil) * Tribanco (Alphaville- Brasil) * C6 Bank (São Paulo - Brasil)