Lenguaje de Programación R Jobs

I have a complete CSV dataset that already contains daily returns, firm characteristics, and simulated ESG scores from six different rating agencies. I need a reproducible R workflow that: • Imports the CSV, fixes any inconsistent data types, and normalises numeric fields where appropriate (the file is already largely free of missing values, so no imputation step is necessary). • Calculates excess returns, firm betas, and then standardises each agency’s ESG rating using Z-scores. • Combines the six standardised ratings into an overall ESG score and derives an ESG-uncertainty measure (e.g. cross-sectional dispersion). • Forms monthly value-weighted portfolios sorted independently by beta, by the combined ESG score, and by the ESG-uncertainty metric. •...

I need a data analytics expert to analyze key datasets. Key requirements include: - Analyze sales, customer, and operational data. - Identify trends, make predictions, and improve efficiency. - Deliver insights for reports, business decisions, and strategy development. Ideal skills and experience: - Proficiency in data analytics tools (e.g., Python, R, SQL). - Strong analytical and statistical skills. - Experience in generating actionable insights from complex datasets. - Ability to communicate findings clearly. If you have a proven track record in data analytics and can work within my budget, I would love to hear from you.

I want to quantify how recent advances in artificial intelligence are influencing forecasts of French GDP. I already have access to long-run historical GDP time-series and would like you to work only with that dataset for now. The task is strictly quantitative: build and compare solid économétriques models that incorporate an IA variable (or proxy) and measure its marginal effect on growth projections. You will be free to choose among standard time-series techniques—VAR, ARDL, error-correction, whatever proves statistically sound—provided the approach is fully documented and reproducible in R, Python, or Stata. Along the way, please explain every transformation, stationarity check, and specification test so that the methodology can be defended in an academic sett...

I want an Android app that SIMULATES crash game behavior for PROBABILITY ANALYSIS purposes. Requirements: - Simulated crash rounds based on probability models - Streak & volatility analysis - Auto-generated signals (Low / Medium / Avoid) - Target outcome accuracy around 75%

I'm looking for a skilled analyst to provide detailed reports on basketball game statistics. The focus will be on: - Player performance metrics - Team performance metrics - Game outcome predictions Ideal skills and experience: - Strong analytical skills - Experience in sports analytics, especially basketball - Ability to create comprehensive and clear detailed reports - Knowledge of statistical software and tools Please include samples of previous work in your bids.

Freelance R Expert Needed: Advanced Signal Processing for Maternal, Fetal & Neonatal Health We are seeking a senior R scientist with deep experience in audio / seismic data, wavelet methods, and Bayesian modeling to help demonstrate that R is just as good as Python at surfacing early physiological health markers. This role is for someone comfortable working below the noise floor—where the signal of interest is subtle, nonstationary, and embedded in the mechanics of living systems. What you’ll work on 1. Signal conditioning & noise removal • Design and evaluate signal conditioning pipelines for low-amplitude physiological data • Implement filtering strategies to remove mains contamination (50/60 Hz and harmonics), including: o Notch / comb filters o Adaptive ...

I have an IRB-approved protocol and SAP psychometric study of a digital cognitive wellness battery Scope of Work (must be included in proposal) Data QC and cleaning Validate export integrity, missingness review, recodes per data dictionary Produce analysis-ready dataset + QC notes (queries list) Primary reliability analysis ICC(3,1) with 95% CI Run two ICC approaches for verification (ANOVA-derived ICC and psych::ICC output) and confirm they match as expected Secondary analyses Domain/task ICCs with CIs Practice effects (paired tests + effect sizes) Usability (SUS/TAM) summary Completion rates, validity flags, session duration Exploratory correlations with SLUMS Deliverables Reproducible R repo (scripts, README, session info, locked outputs) Word-ready statistical report (tables + concise...

At I am expanding an internal project that explores fresh ideas in machine learning and need an intern who can jump straight into the research cycle—formulating hypotheses, building quick prototypes, running experiments, and summarising insights for the team. What you will do • Survey recent ML literature that aligns with our roadmap • Design and execute experiments to test new model architectures or training tricks • Record results, visualise them clearly, and explain the “why” behind the numbers • Iterate on your findings until we have a result worth integrating into production-grade code What you should bring Your application only needs to highlight relevant experience, but that experience must show strong analytical and problem-solving...