- Created Tables, materialized views, queries, and datasets for clients using SQL (Snowflake and PostgreSQL), cleaning and combining data from multiple stores.- Developed dashboards on Quicksight to assess demographics, customer behaviors, store performance, product performance, and inventory, using advanced analytics.- Created calculated fields using aggregate, conditional, table calculation, date, numeric and string functions (avg, periodtodate, distinct_count, coalesce, ifelse, isNull, avgOver, periodoverperiod, rank, windowSum, etc).- Created parameters and included those filters as part of calculated fields, filters, visuals titles and axes, to allow a dynamic and interactive use of dashboards based on client-specific goals.- Developed scripts with Python using AWS SDK Boto3 to automate dashboard creation, removing unused fields, customizing dashboards, and reducing development time.- Developed Forecasting models to predict sales based on SKU, brand and beverage type.- Interacted with other teams to define database requirements for new datasets and dashboards.- Identified best-performing brands and consumer trends in liquor stores, indicating a significant reduction in purchases year over year.- Using POS data and loyalty data, helped clients identify seasonality of products, cannibalization, and direct competitors in the liquor market.

Achievements:• Prepared decision-focused, customer-facing Dashboards that optimized user experience and improved time to action by 66% using Power BI, AWS Quicksight, Tableau, and QlikView.• Designed, implemented, and updated over 100 dashboards and datasets used for Sales, Management, customer experience, and clients.• Developed a CI/CD pipeline using Gitactions to automate dashboard's updates using Python and specific APIs to connect and push changes.• Implemented KNN models with Python to predict pest development over time and prevent the spread of economically impacting pests and diseases.• Performed spatial analysis to identify target metric clusters and provide recommendations • Implemented polynomial regression models to predict growth over time, reducing costs by 75% (More Details: https://bit.ly/3PfZbDC)• Developed and optimized SQL queries, and CTEs in Snowflake, lowering costs by around 50%.• Collaborated in the development of live-alerts tools to inform and help customers prioritize tasks, reducing pest outbreaks.• Performed exploratory data analysis, cleaned, aggregated and tested data to validate queries, tables and Datasets using Snowflake and Python.• Prepared scripts in Python connecting APIs to collect data from Snowflake and other data sources to perform statistical analysis and generate reports.• Interacted with cross-functional teams to understand and design datasets and tables.• Prepared workflows with Python and GitActions, using APIs to automate and expedite deployment of new features.•Co-authored and patented a new Intellectual Property.

Achievements:• Developed a research & development roadmap focused on sustainable forest management with 16 projects, aiming to reduce fertilizer applications, improve employee satisfaction and performance, which ultimately resulted in more uniform and higher yield plantations.• Used statistical analyses to provide cost-efficient recommendations based on ROI• Performed root cause analysis, isolating factors, determining causes, and proposing action plans• Quarterly meetings with technical and non-technical teams, presenting results based on audience. • Reduced fertilizer requirements for seedling production by more than 60% and improved seedling quality by testing and selecting better formulations.• Reduced seedling production time by 33%.• Reduced the number of fertilizer applications in the field by 56 %• Prepared and established over 100 trials using Factorial, RCBD, split-plot and paired designs based on hypothesis and treatments to be tested.• Utilized ANOVA, MANOVA, Mean Comparison (t-Test), and regression analysis to analyze trial data and provide technical recommendations.• Prepared executive summaries for regional managers and directors, final and update reports for clients, and scientific papers and manuscripts for Journals.• Managed a team of 32 researchers and technicians.

Achievements:• Designed surveys and supervised data collection;• Performed Data quality assurance;• Organized periodical meetings with customers;• Presented results to a technical audience with roadmap and timelines;• Prepared monthly update reports; • Established a benchmarking network between competing clients towards the creation of new solutions for the forestry sector; • Monthly meetings on-site with customers.

• Performed Linear and polynomial regression analysis to provide recommendations;• Used ANOVA and Tukey test to compare soil properties;• Designed field and lab experiments;• Supervised undergraduate students;• Presented results in symposiums;• Worked collaboratively with other researchers. • Write scientific and technical papers.

- Quality control assessments on silviculture operations;- Management of quality control and inventory teams;- Monthly Technical performance report based on quality control assessments;- Identification of main performance improvement points for silviculture;- Daily, weekly and monthly reports on harvesting and silviculture machines operational performance;- Time and motion studies for silviculture operations;

-Time & Motion studies for the main silviculture operations in the company;-Weekly report on operational performance;-Identification and recommendation of potential improvements related to weekly findings;-Bi-monthly update presentations to mid and top operational management.Internship allowed the company to identify the main gaps in its silviculture operations and review contractors and payment.