Lenguaje de Programación R Jobs

I’m putting together a comprehensive backtest that focuses exclusively on stock market data from the NYSE and NASDAQ, spanning the last 10 years. To do this effectively I need a well-structured historical dataset that I can drop straight into my models without hours of manual cleanup. Here’s what I’m after: • Daily (or finer) OHLCV prices, fully adjusted for corporate actions, splits, and dividends. • Consistent symbol mapping so delistings, mergers, and ticker changes don’t break the series. • A single, tidy delivery format—CSV files are fine, but a lightweight SQL or Parquet database also works if you prefer. • A short README that explains field definitions, adjustment methodology, and any known data caveats. If you already have a...

I need a skilled data professional to turn my historical sales records into reliable projections for the months ahead. The raw files are already exported from our POS and e-commerce platforms; they cover daily transactions, product categories, promotions, and regional outlets. Your first task will be to explore and clean this sales data, handle any missing values or outliers, and engineer features that capture seasonality, campaigns, and other business drivers. My primary goal is an accurate sales forecast and projection roadmap. I am particularly interested in machine-learning approaches—think gradient-boosted trees, LSTM, Prophet, or any other model you feel best suits the data’s structure. Classical time-series or regression techniques are fine as benchmarks, but the core d...

I need a skilled data analyst to work on a medical retrospective study. The dataset is about 335 patients Key Requirements: - Utilize descriptive statistics and multivariate analysis. - Focus on comparing different groups. - Ideal Skills and Experience: - Proficiency in statistical software (e.g., R, Python, SPSS). - Strong background in statistics and data interpretation. - Experience with retrospective study data and group comparison. Looking forward to your expertise!

I am preparing a full-length manuscript for submission to a Q1 SSCI economics journal on the theme of machine learning–driven economic-growth prediction. The core of the article must showcase concrete applications and real-world case studies rather than abstract algorithmic discussions. I want a genuinely global perspective, so the empirical section should compare or combine economies across different income levels rather than concentrating on a single region. All quantitative work has to rely on publicly available government databases—think World Bank, OECD, IMF, national statistical offices—so that review-ers can easily replicate the results. You are free to merge multiple sources as long as every dataset is openly accessible. Key expectations • 8,000–1...

I am looking for an experienced data analyst / ServiceNow expert to help transform CMDB data into actionable insights and predictive analytics. The CMDB currently receives data from three sources: • Network devices • Software applications • Servers / hardware assets ⸻ Scope of Work: 1. Data Consolidation & Preparation • Review and consolidate CMDB data • Clean and standardise datasets for analysis • Ensure data is usable for reporting and modelling 2. Predictive Analysis • Build simple predictive models to identify early warning signals such as: • Capacity issues • Performance degradation • Configuration drift 3. Dashboards / Reporting / Alerts • Create easy-to-use outputs for operations teams (e.g., dashboard...

? HAGO Contest #2 – April ? For data scientists and analytics enthusiasts, we present a new challenge with Amazon sales dataset. ? Tasks: Explore the dataset in depth Analyze patterns and trends Build a predictive model using Python Submit results in a PDF file within our private community ? Prize: The winner receives $15 USD for the best analysis and prediction ? Don’t forget to join the IFAI Contest for future forecasting, where the winner earns $10 USD. ✨ Tips to increase your chances of winning: Make your analysis comprehensive yet easy to understand Add clear and insightful visualizations Focus on prediction accuracy and creative ideas

Strategy Name: Footprint Dot-Based Auto Exit Strategy (Profit-Constrained) (DOT indicator referenced already has been built) $30 Flat. ______________________________________________________________________________________________________________________________________ 1. Purpose This strategy is designed to: Automatically exit manually placed positions (Long and Short) Based on pre-existing footprint indicator signals (Red and Blue dots) Ensure that ALL exits are profitable Operate on a Line Break chart Process both historical and real-time data ________________________________________________________________________________________________________________________________________ 2. Dependencies Requires an existing indicator that provides: Red Dots Plotted on positive (up) ...

I need a dependable way to capture every alteration that occurs in a trading broker’s data feed and keep a clear audit trail of those changes. The broker has not been chosen yet—Interactive Brokers, TD Ameritrade, or E*TRADE are all on the table—so the solution must remain flexible enough to plug into any of their public APIs or downloadable reports. The fields I will most likely focus on are execution-related: timestamps, quoted prices, and volumes; however, I want the workflow to be able to monitor any additional columns that might prove useful later. In practical terms, I expect a repeatable script (Python, R, or another language you recommend) that can: • Connect to the selected broker’s API or data export • Take regular snapshots or pull historica...

I’m looking for someone who can turn our raw internal database records into forward-looking insights. The data is already well-structured in SQL tables; what I need now is a predictive layer that helps us forecast key metrics and identify the drivers behind them. You’ll have direct read-only access to the relevant tables along with a short data dictionary. From there, please choose the techniques and tools you’re most comfortable with—whether that’s Python (pandas, scikit-learn), R, or another established machine-learning framework—so long as the final model is reproducible and the code is clearly documented. The deliverable I expect is a concise notebook or script that: • cleans and preps the data, • trains and validates at least one...

analysis of variance (ANOVA) and regression analysis. Key requirements: - Analyze numerical and categorical data - Identify relationships between variables - Provide detailed interpretation of results Ideal Skills: - Proficiency in statistical software (e.g., R, Python, SPSS) - Strong background in statistics and data analysis - Experience with complex datasets - Ability to explain statistical concepts clearly Please ensure you have relevant experience and skills.