English:
Advanced
Laura O. N.
Vetted by YouTeam
Colombia
UTC -05:00
America/Bogota
English:
Advanced
I am a statistician with experience in the role of data science, performing descriptive, inferential, predictive, and cognitive statistical analysis
I am a statistician with experience in the role of data science, performing descriptive, inferential, predictive, and cognitive statistical analysis of analytical projects for various sectors, relying on the programming languages Python, and R for data analysis, data mining platforms such as Knime and visualization tools such as PowerBI, Shiny, and Plotly. All this is under the framework of agile Scrum methodologies for the development of analytics project life cycles based on CRISP-DM. I am finishing a Machine Learning Scientist career track in Datacamp and at this moment I’m studying MLops and AWS cloud practitioner in Udemy.
Want to hire this engineer?
Check if Laura O. is availableExpertise
Years of commercial development experience
6 years of experience
Core technologies
Project Highlights
Mach learning
Mercado libre
Data Analysis: Extract and manipulate large datasets from Mercado Libre's platforms, deriving valuable insights to enhance user experience and business strategies. Machine Learning: Develop predictive models for personalized recommendations, fraud detection, and demand forecasting, contributing to platform efficiency and customer satisfaction. A/B Testing: Design and analyze experiments to optimize product features, pricing, and marketing campaigns. Data Visualization: Create informative dashboards and visualizations to facilitate data-driven decision-making.
Responsibilities & achievements
As a Data Scientist at Mercado Libre, you will play a pivotal role in transforming raw data into actionable insights. Collaborate with cross-functional teams to uncover patterns, trends, and opportunities within the vast ecosystem of Latin America's leading e-commerce platform. Your expertise will drive innovation, enhance customer experiences, and fuel business growth.
Bank statistics
Banco de Occidente
Support decision-making through statistical modeling and/or Machine Learning algorithms under the CRISP-DM methodology for financial institutions on issues such as customer loyalty, and customer segmentation by type of transaction, among others.
Responsibilities & achievements
Statistical Modeling: Apply advanced statistical techniques to analyze financial data, providing actionable insights that aid decision-making. Machine Learning Algorithms: Develop and implement ML algorithms following CRISP-DM methodology, addressing challenges like customer loyalty and transaction-based segmentation. Data Preparation: Collect, clean, and preprocess data for modeling, ensuring its accuracy and relevance. Customer Loyalty Analysis: Explore and interpret customer behavior patterns to enhance loyalty strategies and retention efforts. Segmentation Strategies: Utilize transaction data to create meaningful customer segments, enabling targeted marketing and personalized services. Collaboration: Work closely with cross-functional teams to understand business needs and translate them into effective data-driven solutions. Model Evaluation: Assess model performance and iterate to improve accuracy and effectiveness. Documentation: Document methodologies, data sources, and results for clear communication and future reference. Stakeholder Communication: Present findings and recommendations to stakeholders, facilitating informed choices in financial strategy.
Data360
Participation in projects in various sectors supporting business decisions in Machine Learning and Deep Learning models, from the earliest stage of the analytical project, transmitting business results to both customers and stakeholders through analytical dashboards composed of the results obtained through descriptive, inferential, predictive, and cognitive statistics
Responsibilities & achievements
Project Engagement: Contribute to diverse projects across sectors, engaging in the complete lifecycle of analytical initiatives. Machine Learning Expertise: Provide expertise in developing Machine Learning and Deep Learning models to drive informed business decisions. Early Project Stage: Engage from project inception, collaborating with teams to define objectives and establish data requirements. Analytical Dashboards: Design and construct analytical dashboards that showcase results obtained through descriptive, inferential, predictive, and cognitive statistics. Business Insights: Extract valuable insights from analytical findings, translating them into actionable recommendations for business strategy enhancement.
Personalsoft
Support and development of hard rule algorithms and predictive models in Machine Learning, Deep Learning, and classical statistical models projects to provide solutions to different sectors such as financial, health, and technology, among others
Responsibilities & achievements
Algorithm Development: Create and enhance hard rule algorithms, predictive models using Machine Learning, Deep Learning, and classical statistical approaches. Cross-Sector Solutions: Provide tailored solutions across various sectors (finance, health, technology) by adapting algorithms to meet unique challenges.
Education
Higher education in Computer Science
Agency
50-100
GMT+13
Argentina
Core Expertise
Want to hire this engineer?
Check if Laura O. is available