Nayane .

Data Scientist

Data Scientist Specialist
10/1/2023 - Present

Leads the Advanced Analytics stream, managing a team of five data scientists. Focuses on developing business solutions through A/B testing, time series analysis, and statistical modeling. Utilizes expertise in image modeling, generative AI, and prediction/forecasting methodologies. Employs machine learning techniques, including regression and classification, to drive data-driven decisions and strategic insights.

Senior Data Scientist
4/1/2022 - 10/1/2023

Achieved notable advancements in data science projects within the industry, including a 3% reduction in fuel consumption for harvesters through optimized additive product selection and a 7 T/ha increase in sugarcane productivity by utilizing superior fertilizers based on historical data analysis. Identified key agronomic indicators to mitigate failures in sugarcane fields, contributing to enhanced long-term productivity, and improved the precision in selecting sugarcane varietal clones, resulting in increased productivity and potential long-term ROI.

Delivered data-driven solutions in agribusiness, encompassing digital agriculture, remote sensing, agronomic experimentation, and predictive modeling for sugarcane productivity forecasting. Enhanced supply chain operations by defining product purchase strategies through statistical analysis and increasing yields using A/B testing methodologies. Effectively communicated analytical outcomes to stakeholders and spearheaded change management initiatives when necessary. Addressed business challenges through interdisciplinary collaboration and currently lead the Advanced Analytics II track, which focuses on developing business solutions using A/B testing, time series analysis, and statistical modeling.

Utilized a range of tools and technologies including PostgreSQL, DBeaver, AWS, Python, R, DataBricks, and PowerBI. Applied methodologies like CRISP-DM and incorporated design sprints using SCRUM to streamline project execution.

Data Scientist
7/1/2021 - 4/1/2022

Developed analytical solutions for business problems utilizing big data, particularly in the agriculture sector with a focus on sugarcane. Designed and architected solutions to address complex business challenges. Gained expertise in utilizing PostgreSQL for structured data management and AWS for comprehensive big data solutions. Proficient in using DBeaver as a database management tool. Strengthened skills in Python and R for data analysis and statistical computations.

Content and Project Contributor
3/2/2021 - 12/1/2021

Served as a content creator and developer for data science and artificial intelligence projects aimed at the community and beginners. Responsibilities included training trainees in machine learning, exploratory data analysis, data visualization, and big data. Established partnerships with multinational corporations to develop and implement business-oriented solutions. Focused on solving complex problems and generating innovative ideas that could be incorporated into business strategies.

Ambassador and Leader
10/2/2020 - Present

Led and trained a team of 10 individuals, overseeing data science projects focused on agronomy and related fields. Organized an event that attracted over 500 participants, resulting in significant partnerships with multinational companies and receiving positive accolades from the general public.

Data Science Researcher
3/2/2019 - 11/1/2022

Led the research project Sustainability of Crop-Livestock Integration Systems Evaluated by Artificial Intelligence, focusing on the application of diverse machine learning and statistical modeling techniques. Managed and analyzed data for the FAPESP project, dealing with a substantial dataset of over 10,000 entries gathered from field projects. Successfully created and implemented more than five innovative solutions, which garnered awards and resulted in high-impact international publications.

Collaborated with NASA to conduct various activities involving map building using the Python programming language, aiming to predict productivity and soil moisture levels. Developed an online structure capable of estimating soil water content in real-time, achieving a 90% reduction in electricity expenses during the planting phase of large agricultural commodities. Additionally, created an interactive map of Brazil for data visualization purposes using Python.

Junior Research Scientist
3/2/2017 - 7/2/2018

Executed and maintained field experiments focused on soil fertility analysis, quantifying soil carbon and nitrogen for enhanced plant absorption to reduce chemical fertilizer use and costs. Coordinated ongoing project testing various artificial intelligence techniques and data analysis methods, handling a significant BIG DATA repository of over 10,000 collected and quantified field data points. Developed technical expertise in soil chemistry analysis and AI-driven data analytics. Utilized advanced statistical tools and frameworks to ensure data accuracy and interpretability.

Agricultural Engineer at Federal Institute of Pará - Campus Castanhal
2012 - 2017

Agronomy at São Paulo State University - Jaboticabal Campus
2019 - 2022

Data Science at South American Institute for Fundamental Research - UNESP, Brazil
2019 - 2019

Data Science at International Centre for Theoretical Physics - University of Trieste, Italy.
2020 - 2020

Artificial intelligence and Machine Learning at Huawei certification
3/2/2021

Python and Machine Learning at International Telecommunications Society
11/2/2020

Use of Remote Sensing and Artificial Neural Networks in Agriculture at UNESP
11/1/2019

Certificate of Spanish at TESE Prime
10/1/2019

Soil Science Data Analysis in R at UNESP
7/1/2019

Statistical Modeling of Agricultural Phenomena: Fitting and Evaluation of Linear and Non-Linear Models at UNESP
8/1/2017