At NTT Data, I led the optimization of critical data processing flows and solution migration, successfully transitioning processes from Oracle to Azure by leveraging reverse engineering to decode intricate business models.Key Contributions:• Field Analysis and Abstraction: Utilized Cloudera and advanced SQL to review and abstract essential data fields, improving data accuracy and accessibility.• Process Orchestration: Developed and managed network groups, job schedulers, and orchestrated processes with Jenkins and Bitbucket, enhancing operational efficiency.• Automation and Deployment: Designed and deployed automated workflows using Azure Function App, reducing production deployment times by 30%.• Agile Collaboration: Employed agile methodologies to collaborate with diverse, multidisciplinary teams on strategic projects, driving them to completion.• Script Optimization: Optimized scripts and created custom queries using PySpark and Databricks, automating complex processes and saving an estimated 20% in processing time.Soft Skills:• Strong problem-solving abilities and analytical thinking.• Effective communication and collaboration within cross-functional teams.• Adaptability to fast-paced and dynamic work environments.• Proactive approach to continuous learning and professional development.

At Credicorp Capital, I enhanced big data processing using Databricks and PySpark, showcasing my proficiency in designing, developing, and maintaining data pipelines. I employed T-SQL, PySpark, and DataVault 2.0, alongside DataFactory, to ensure top-tier data quality. Implementing agile methodologies such as Scrum, Kanban, and DevOps, I streamlined the efficient delivery of data pipelines.Key Achievements:• ETL Optimization: Reduced processing time from 7 days to just 5 minutes, significantly boosting efficiency.• Investment Portfolio Enhancement: Improved the quality of investment portfolios through DataVault 2.0 modeling and advanced analytical models, delivering substantial benefits to Credicorp Capital.Soft Skills:• Strong analytical and problem-solving abilities.• Effective communication and collaboration within cross-functional teams.• Adaptability to fast-paced and dynamic work environments.• Proactive approach to continuous learning and professional development.Technical Expertise:• High proficiency in cloud computing.

• I developed a data analysis platform on DataBricks and PySpark, leveraging DataFactory, which significantly reduced query time for customer data. By migrating Excel visualizations to DataBricks, I achieved a 60% improvement in query time. This platform not only streamlined the querying process but also enhanced the amount of data that could be processed. The system seamlessly connected to a datalake, enabling queries with various data from different banking clients.• Installation and maintenance of monitoring software: I showcased my proficiency in installing and upkeeping monitoring software based on SQL and .NET. This involved implementing robust security measures, which played a pivotal role in assuring clients about the safety of their sensitive data and financial resources. By actively participating in the ongoing maintenance of the monitoring system, I contributed significantly to the overall success of the company, fostering a secure and trustworthy environment for our clientele.

• Guided students in embedded systems programming with C++ and VHDL, fostering positive learning and promoting future engineers.

• Implemented a Mask R-CNN model for medical image pattern recognition, with an accuracy of over 90% in identifying and segmenting organs, using a pre-trained R50-FPN model and a dataset of annotated images.Skills developed:- Advanced knowledge in medical image processing and pattern recognition.- Skills in Python programming and implementation of artificial intelligence models.- Acquisition of experience in the research and application of artificial intelligence in the field of robotic surgery.

Developed a novel algorithm for extracting ionosphere characteristics from photos using Computer Vision, resulting in a 19% improvement in ionogram curve segmentation compared to the current method with an impressive 79% efficiency.Achieved a significant breakthrough by accurately identifying the F region of the ionosphere with an average efficiency of 60%, marking a significant advancement in ionogram scaling technology.

Deep Analysis of Genetic Expression in Schizophrenia and Bipolar DisorderAs a Data Scientist, I conducted a detailed analysis of genetic expression in patients with schizophrenia and bipolar disorder using advanced bioinformatics techniques in R-Studio.I identified common patterns of genetic expression between these two psychiatric conditions, confirming that they share a similar molecular and genetic basis.

• Designed and Designed a low-cost, portable radar system using Python/JS with cost savings of 96% compared to previous laptop-based system.• Implemented acquisition, processing, and data visualization codes on a Raspberry Pi Zero that processed 150 signal data per second.Skills developed:- Advanced knowledge in the operation of radar and electromagnetic wave systems.- Programming skills in Python and JavaScript- Improved ability to design and build hardware and software systems.

Transforming EEG Data into Actionable Insights Using Cutting-Edge Neural Network TechnologyAs a Data Scientist, I transformed EEG data into actionable insights using cutting-edge neural network technology, achieving improved state analysis and decision-making.I reached the highest efficiency of 91.7% using the "traingd" algorithm with 256 FFT points.