Helping startups succeed in their AI journey.I specialize in empowering startups to leverage AI for scalable growth and innovation. With a passion for transforming cutting-edge technology into practical solutions, I guide entrepreneurs through the complexities of AI implementation, from ideation to deployment.Are you a founder? Get in touch!

Focused on AI, Machine Learning, and Data Science.

Angel Investor in one of the largest startup accelerators in Brazil, with more than 100 invested startups, 300 investors and R$ 22 million (USD 4.4 million) invested.

Teaching AI, Data Science and Analytics for the Service Design Postgraduate Program.

A worldwide organization with more than 200 chapters in 60 countries with more than 100k members that promotes diversity in the R community in a friendly and safe environment. More info here: rladies.org

Our mission is to increase the representation and participation of minority groups in AI. ai-inclusive.org/

Reporting to the Global Chief AI Officer (Seth Dobrin) - VP of Data & AI https://www.linkedin.com/in/sdobrin/• Drove IBM’s mission to establish Watson as the leading AI for Business by increasing brand relevancy, mindshare, and share of voice in the AI industry.• Founded and led the Watson Innovations Program, which surfaced and highlighted IBM’s AI innovations through engaging, hands-on user experiences.• Hired, built, and managed an interdisciplinary team of data scientists, UX designers, back-end and front-end developers, and project and product managers.• Established and scaled a pioneering team and program within IBM’s Data and AI organization, driving AI innovations from the ground up.• Defined and articulated the team’s mission, vision, and strategic roadmap, ensuring alignment with organizational goals and delivering high-impact solutions.• Collaborated cross-functionally with IBM Research, Marketing Insights, and Communications teams to address gaps in AI perception and improve IBM’s competitive positioning in the AI market.• Partnering with IBM Research and other parts of IBM to translate the innovations via a handson experience.• Advised cross-functional Data Science and Product teams, shaping strategic roadmaps, introducing new features, and implementing best practices in hiring and employee retention, significantly improving team performance and satisfaction.• Collaborated with key stakeholders across Research, Product, and other divisions, fostering a culture of innovation and cross-functional synergy.• Mentored and coached team members on their projects, enhancing their skills and contributing to the wider data science community through knowledge sharing and best practices.• Led and executed a high-profile Hackathon in collaboration with the University of Florida, engaging over 7,000 participants and achieving an external reach of 1.5 million through strategic partnerships and event promotions.

Responsible for hiring, building, and managing a diverse team of open source developers working on Data & AI projects. Top committers on projects like Tensorflow, Pytorch, Apache Arrow, and Jupyter were on my team.Key External Open Source projects: Tensorflow, PyTorch, Apache Arrow, Apache Spark, Jupyter, JupyterLabSome responsibilities:• Hired the most diverse team in the organization• Managed and led 15 open-source developers working on Data & AI Open Source projects, including Tensorflow, PyTorch, Apache Arrow, Spark, Jupyter, JupyterLab, Trustworthy AI, Elyra, Model Asset Exchange, Data Asset Exchange• Defined roadmap, vision, and strategy aligned with the company's priorities and create metrics to evaluate the team's impact • Created open-source ecosystems: from projects idealization to building communities• Worked closely with business units throughout IBM to ensure that product teams derived value from open source data science and AI technologies• Coached and mentored several folks inside and outside the team on career development, leadership, open-source, allyship, etc

• Managed and led the Machine Learning team working on Open Source Projects • Team members were committers of different open source projects such as TensorFlow, PyTorch, Apache Arrow & Apache Spark • Led the R version of the Trusted AI toolkit (AIF360): the most used and most comprehensive fairness open source toolkit.

Highlights: - Created and presented technical content at key Conferences (ODSC, OSCON, Open Source Summit, Grace Hopper Conference, DataScienceGO)- Launched new open source projects: 1) MAX - Model Asset eXchange: place where you can find and use free open source deep learning models for text, image, audio, and video processing and much more. The curated list includes deployable models, which you can run as a microservice locally or in the cloud on Docker or Kubernetes, and trainable models where you can use your own data to train the models. 2) DAX - Data Asset eXchange: online hub for developers and data scientists to find free and open data sets under open data licenses.- Improved existing core open-source frameworks in AI like Tensorflow

• Built and led a high-performing team of Data Scientists and Data Engineers, driving innovation and delivering actionable insights. • Automated 80% of manual reporting through Shiny dashboards and optimized data pipelines with Amazon Redshift and Jenkins, boosting efficiency by 50%. • Spearheaded end-to-end data science projects, improving delivery timelines by 25%, and developed internal R packages, reducing development time by 70%.

• Delivered floor price optimizations within the first 6 months, increasing publisher revenue by over 20%• Built data science pipeline using Spark (PySpark) - from raw logs to data-ready to model• Developed A/B testing framework and experimentation ecosystem • Designed and implemented the company’s first real-time experiment from the ground up• Worked with 100GB+/day using tools such as Spark and H2O

• Led a team of 5 Data Scientists• Work on pre and post-sales engagements with several clients including Finance, Healthcare, Advertising, etc.• Create the appropriate analytics workflows that best deliver relevant insights and predictive models for a client by applying techniques such as machine learning and statistical analysis to deliver business value.• Train customer teams on best practices for data analysis/modeling within Alpine's software

Teaching Assistant in the Information Design I (DAI 523) class lectured byPino Trogu. This class was an introduction to data visualization with an emphasison best design practices

Main Projects:• ESCALA (Estudio de Salud y Contaminación del Aire en Latinoamérica):Multicity Time-Series Study in Latin America - funded by HEIExamined the association between daily levels of air pollution and mortalityin Mexican, Brazilian, and Chilean cities. This study also evaluated whethersocio-economic status influences the relation between air pollution andmortality.• EpiR: a graphic user interface based on R oriented to epidemiological dataanalysis - supported by the Brazilian Ministry of Health.