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I’m a biostatistician and statistical programmer with four years of experience transforming messy, complex datasets into clear, actionable insights. Whether you're a startup needing dashboards, a small business looking to make sense of your customer data, or a researcher needing statistical analysis, I'm here to help. My toolbox includes: - Languages & Tools: R, SAS, Python, SQL, and Excel - Skills: Data wrangling, visualization, statistical modeling, automation, reporting - Experience: Survey data, time-series, A/B testing, dashboards, public health data, and more I’m especially good at: - Cleaning and structuring raw data to make it analysis-ready - Building intuitive dashboards and data visualizations - Running regression models, classification algorithms, and predictive analytics - Writing clear, understandable reports—even for non-technical audiences - Delivering on tight deadlines with a collaborative, responsive approach 📌 Bonus: I’m bilingual (English & Spanish), detail-oriented, and love solving problems that others find overwhelming. Let’s turn your data into decisions. Reach out and let’s chat about your project!

I am a Statistical Consultant and MS Statistics student at UC Davis. I also received a B.S. in Applied Mathematics/Economics and a Minor in Business Analytics from the University of California, Riverside. 🏆 Elite Credibility: My coauthored research has been selected for presentation at premier national conferences, including: 1️⃣ 2025 Association for Public Policy Analysis & Management (APPAM), Seattle, Washington 2️⃣ 2025 Population Association of America (PAA), Washington, D.C. 📈 Specialized Statistical Services: I leverage R, Stata, and Python to solve complex causal and predictive problems: ✅ Descriptive Regression Analysis: Linear/nonlinear regression, probability modeling (LPM, logistic), ANOVA (One-Way, Two-way, Random / Fixed / Mixed Effects) ✅ Causal Inference: Difference-in-Differences (DiD), Instrumental Variables (IV), and Panel Data (Random / Fixed / Mixed Effects) ✅ Predictive Modeling: Machine Learning (Gradient Boosted Trees, Random Forest, KNN) ✅ Survey Methodology: Expert population weighting, clustering, and post-stratification ✅ Statistical Tests: A/B tests, T-tests, Chi-squared Tests, Hausman test, etc. Some Projects: 1️⃣ Github Website (with an interactive dashboard using PostgresSQL and Python, portfolio, and other webpages on reproducible research) 2️⃣ Regression Analysis of Airbnb prices in Mexico 3️⃣ Regression Analysis of H-1B sponsor rates by industry type and location In a year-long data analytics intern position, I: 1️⃣ Created and implemented a database into our center's initiative on analyzing academic technology usage. 2️⃣ Reached out to technology vendors of the university, requesting data extracts and communicating with them on the interpretation of data. 3️⃣ Streamlined data collection, and organized all data into a database that is still used at the center. 4️⃣ I cleaned and prepared several spreadsheets with hundreds of thousands of rows within Google Sheets, and provided key metrics through dashboards and reports in Google Looker Studio. 5️⃣ I connected this data and made it accessible through Slack. I reported on my progress through Slack, Asana, and Zoom meetings (disseminating findings through bi-weekly meetings). 6️⃣ I implemented data governance policies and facilitated meetings on data governance. 7️⃣ I wrote, recorded, and hosted trainings for my colleagues in Looker Studio. 8️⃣ Providing data-driven insights through story-telling. 🛠 Technical Toolkit: Languages: R, Python , SQL (PostgreSQL), Stata. Visualization: Plotly, ggplot, Looker Studio

Are you in search of a skilled and detail-oriented statistician and data analyst who has the right domain knowledge to extract accurate insights from your research, survey, electronic health records, randomized controlled trials, development programming, and business data? If yes, you have come to the right profile. I am a data analyst with over ten years of experience in working with various tools such as Excel, Stata, R, Python, SAS, and Power BI. I am not only interested in working with data but also enthusiastic about the stories and insights that it can reveal, particularly if such findings can contribute to business and policy decisions. While a typical analyst may view data in terms of numbers and values, I will collaborate with you to identify the relevant econometric models based on the domain knowledge to analyze your dataset accurately and provide valuable insights. I possess subject matter expertise in education, engineering, sales, healthcare, gender, and international development. Therefore, you will be hiring someone who can personalize your project through a deep understanding of your dataset. I possess expertise in multiple areas, including: → Designing and analyzing surveys using techniques such as stratification, clustering, weighting factors, design effects, etc. → Designing and analyzing randomized controlled trials → Conducting descriptive, predictive, and inferential statistical analysis → Cleaning and mining data using Stata, R, Python, and SAS → Performing regressions such as OLS, polynomial, logit, probit, ordinal, multinomial, Heckman, etc. → Using regularization regressions such as ridge and lasso → Applying count models regression techniques such as Poisson, negative binomial, zero-inflated, etc. → Using instrumental variable regression, panel data regression, and time series analysis → Conducting principal component and factor analysis → Performing survival analysis using techniques such as censoring, survivor function, Cox regression, Kaplan-Meier curves, and hazard function → Interpreting results in detail and writing reports on findings. Let me know if you have any further questions or if you need any assistance with any of these areas. Get in touch with me at let’s bring your project to life in the shortest possible time.

Biostatistician of 3 years with 13 years of collective data analysis experience and proven track record of delivering data-centered narratives (15 published articles) in diverse disciplines from -omics to healthcare research. My go-to tool is R/R-studio, I favor Bayesian methods, and I take pride in delivering expert-level services. Expert-level services: * Data management, analysis, and visualization * Review and editing academic writing (protocols, posters, abstracts, manuscripts, dissertation) * Study design consultation (power analyses, Bayesian operating characteristics) * 1:1 mentorship and training on R coding, research methods, project management, data management Skills: R/R-studio, Data analysis, Project management, Database development (REDCap expert), Dashboards (PowerBI) , Data wrangling, Bayesian methods, Monte Carlo Simulations, Causal Inference (propensity scores, standardization, difference-in-difference-DiD, synthetic controls) Credentials: * Practicing biostatistician that leads clinical trials, observation, and quality improvement studies in the area of oncology at a cancer institute * PhD in quantitative biology * 16 peer-reviewed publications in the areas of surgical oncology, medical oncology, quantitative genetics, evolutionary physiology, genomics, gene expression, and study design.

I'm a software developer with data science experience across multiple platforms. For data science work, I primarily use R and python but I have experience with a few different tools (listed below). I have experience with data visualization and manipulation - specifically using d3.js in combination with R to create a web interface to explore aggregated metrics in a medical context. I've completed various types of GIS projects - from heatmapping customer bases to creating interactive maps with custom data. Through my computer engineering education I was exposed to a variety of programming languages in different contexts - from web design to microcontroller development. I'm very adaptible and I love learning so I have experience with a number of platforms and tools. I've listed some below. Languages: R, python, C++, Java, javascript Specialties GIS: leaflet.js, d3.js, ArcGIS Visualization: d3.js, ggplot2, RShiny, Tableau

Skills -Data management and Statistical Analysis -Academic, Scientific, and Grant Writing -Software and language Proficiencies- R, C# ,SPSS, SQL, Excel, Unity I am a Ph.D. Research Psychologist with a focus in advanced quantitative and experimental methods. I also completed a post-baccalaureate certificate in applied statistics. I have experience with advances statistical methods including ANOVA, regression, structured equation modelling, multi-level modelling, meta-analyses, as well as more basic analysis and visualization. I also have extensive experience working in advanced data management and automating data transformation and cleaning in health and research settings. I have provided data analysis consultation services and support for research in a variety of disciplines including nursing, marine science, public admisntration, archeology, fine arts, and biostatistics I have extensive skill and experience in R, SPSS, SQL, and excel. I am also familiar with work flow management tools like GitHub, Jupyrter notebooks, and Google CoLab. I am proficient in scientific wring and have several peer re-viewed publications. I have successfully submitted Grants to different funding agencies including the National Institute of Health.