Justina Petraityte
About
Detail
Developer Relations Engineer | Technical Educator | AI and Web3
Portugal
Résumé
Jobs
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Senior Developer AdvocateBufferApr 2026 - Current (5 months)- Developer Relations EngineerLava NetworkJan 2025 - Apr 2026 (1 year 4 months)- Driving the adoption of Lava Network products (Public Lava RPC, Lava RPC API) - Establishing and fostering technical collaborations between Lava Network and other web3 projects and ecosystems - Fostering Lava RPC Node Provider community - Creating technical documentation, tutorials, video content - Representing Lava at developer-focused events and hackathons, live events and AMAs
- Developer Relations EngineerRasaSep 2023 - Apr 2025 (1 year 8 months)Projects: • 11-episode video content series covering building conversational AI assistant's with Rasa's CALM framework (Conversational AI with Language Models). • Rasa AI Agent Building Challenge - 1 month online hackathon, 300 builders. Was responsible for planning the executing the event from defining the challenge to providing technical support for the builders. • Live coding workshops and technical tutorials for building AI agents using Rasa tools
- Developer Success LeadBox LabsApr 2022 - Oct 2024 (2 years 7 months)- Hired and managed a Developer Success team of 3 people - Built developer onboarding strategy for an early-stage product - Built technical demos to showcase the features of the product - Created technical documentation and technical guides(written and video) to educate developers on topics related to Ceramic and web3 - Led live coding workshops at conferences like EthDenver and EthCC - Built product adoption strategy and collaborated with the product team on user feedback-driven product improvements
- Head of Developer Relations - Conversational AIRasaMay 2019 - Apr 2022 (3 years)- Hired and managed a 4-person Developer Relations team - Built a developer education and developer community growth strategy - Created a 12 episode online course on developing conversational AI assistants with Rasa tools (250k+ views) - Created technical tutorials (video and blogposts) on machine learning behind conversational AI assistants and Rasa Open Source features - Gave 30+ talks and live coding workshops on machine learning and conversational AI at developer conferences around the world - Contributed to the core improvements of the Rasa's open source product through the collected feedback from developer teams
- Developer Advocate - Conversational AIRasaMay 2018 - Apr 2019 (1 year)- Bootstrapped the open source Rasa community from a few hundred members to tens of thousands of developers using Rasa around the world - Gave 30+ technical presentations and workshops on building conversational AI assistants at developer conferences in Europe and the US - Led the developer education on conversational AI: created technical tutorials, demos, video content - Built projects and demos with Rasa Open Source and other tools - Implemented automatic Rasa open source community tracking and reporting - Hired and managed +1 member on Developer Relations team
- Senior Data ScientistRadiant WorldsJul 2017 - May 2018 (11 months)• Developed and deployed in production item-based and user-based recommendation engines for comic books • Developed and deployed in production a machine learning powered conversational assistant for data reporting, capable of fetching, summarising, visualising data through natural human language conversations on Slack. • Developed an offensive language detection model for an in-game chat. • Managed junior members of BI team.
- Senior Data AnalystRadiant WorldsJan 2016 - Jun 2017 (1 year 6 months)• Implemented player retention prediction model using a stack of XGBoost, LightGBM, GBM, Random Forests, SVC models. • Implemented Mixture of Gaussians Clustering model for clustering game players based on their play style • Implemented Machine Learning algorithms to predict the features of game players – gender, occupation, collaboration with other players. • Developed a system of interactive Sankey diagrams for in-depth churn analysis. • Designed and managed telemetry data dashboards on Tableau and Tableau Server. • Was responsible for KPI ad-hoc analysis and reporting to stakeholders of the company
- Junior Data AnalystDatacticsJul 2015 - Jan 2016 (7 months)• Worked on design, implementation, and testing of data quality management projects for financial data using company's in-house developed tool FlowDesigner. • Implemented and managed dashboards for Data Quality Management using QlikView. • Worked on analysis of big volumes of data focusing on data cleansing, normalization, fuzzy matching.
- Business AnalystSeesam Insurance AS Lietuvos filialasDec 2014 - Jun 2015 (7 months)• Developed a predictive model for forecasting insurance risk premiums. • Worked on an in-depth analysis of company’s insurance products (on the National and Baltic States level). • Was responsible for KPI reporting to stakeholders and managers of the company.
- Intern - Junior Data AnalystMarkMonitorJun 2014 - Aug 2014 (3 months)• Processed information on internet piracy related data • Performed data verification using Excel and company‘s in-house developed tools • Gained experience in collecting, cleansing and managing big volumes of data using Excel • Gained theoretical and practical knowledge on internet piracy trends and digital content
Education
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- Bachelor's degree, EconometricsVilniaus universitetas Vilnius UniversityJan 2011 - Jan 2015 (4 years 1 month)
Projects (professional or personal)
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- EEconometric Modelling of Car Insurance Claims Cost (BSc Thesis Project)Feb 2015 - May 2015 (4 months)Non – life insurance pricing using econometric methods. Statistical analysis of claim frequency and claim severity using different rating factors. Claim frequency was estimated using Poisson GLM, Negative Binomial GLM and ZIP models. GLM Gamma model was applied for claim severity data. Using claim frequency and claim severity models risk premiums were estimated.
- EElectricity demand econometric modelling (BSc Course Project)Sep 2013 - Dec 2013 (4 months)Econometric modelling and forecasting of daily and hourly electricity demand in Lithuania. Electricity consumption was estimated using SARIMAX models using calendar and weather variables as regressors.
Awards
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- Third - degree diploma in Econometric CompetitionVilnius UniversityThird place in Econometric Competition organised by Vilnius University, faculty of Mathematics and Informatics. Awarded for prediction of the effects of Euro adoption on prices in Lithuania.
- Top 11% at Porto Seguro’s Safe Driver Prediction Kaggle CompetitionKaggleKaggle Data Science competition for predicting the probability that a driver will initiate an auto insurance claim in the next year. The final model was a stacked model consisting of LightGBM, XGBoost, CatBoost as base models and a Logistic Regression model as a model used for stacking.
- Top 22% at Predicting Red Hat Business Value Kaggle competitionKaggleKagglers were challenged to create a classification algorithm that accurately identifies which customers have the most potential business value for Red Hat based on their characteristics and activities. My final solution contained an ensemble of XGBoost, Random Forests, GBM, AdaBoost, Decision Trees, KNN and SVM algorithms.
- Top 18 % at Two Sigma Connect: Rental Listing Inquiries Kaggle competitionKaggleKaggle Data Science competition for predicting the number of inquiries a new listing receives based on the listing’s creation date and other features. The data was issued by RentHop and contained numerical, text data as well as well pictures of the listed properties. My final solution contained an ensemble of XGBoost, LightGBM, GBM, Random Forests and SVM.
- JEU Young Scientist National Competition second - degree diplomaJan