Ventas de Big Data Jobs

Data Analyst Tutor Needed — Intensive 2-Month Program (Python, SQL, Excel, Power BI) Overview I'm looking for an experienced data analyst or data scientist to tutor me through a structured, self-directed curriculum over the next 2 months, with the goal of being fully job-ready and actively applying for Data Analyst roles by the end of the program. I already have a Master's degree in Data Science and have built out a complete week-by-week study plan — I need a tutor to guide me through it, review my work, unblock me when I get stuck, and run mock interviews at the end. This is not a "teach me from scratch with your own materials" role — I have the curriculum already mapped out day by day. I need someone who can teach to that curriculum, adapt it if ne...

Machine Learning Pipeline – Job Market Analytics & Salary Prediction Created an end-to-end machine learning pipeline for looking at job market data and guessing what salaries might be. Key Features: Worked on. Fixed 10,000 or more job-market records using Python, Pandas and NumPy. Made an automated ETL/data preprocessing pipeline to take care of data cleaning, changing data making it all the same and checking if it is all the same. Added a PostgreSQL (Neon) database to keep data in a good way and help with machine learning work. Did analysis of the data. Looked at the features to find what helps predict salary. Trained a Random Forest regression model to guess salaries. Found that employee_residence is one of the things to use for guessing salaries. Built a Fas...

The Job Post Blueprint (Copy & Paste) Job Title: 1-Time Cloud Deployment (FastAPI + Python + SQLite) Salary Type: Fixed-Price /milestone based TaskTurnaround Time: 4 to 5 Days Experience : 0 to 3 years freshers,juniors, specialist Job type: freelancing/hybrid/remote Project Overview :We have built Project Ed, an enterprise-grade behavioral AI cybersecurity framework designed for online education platforms. The application’s core backend logic is 100% complete, fully tested, and consolidated into a single working file. The codebase features a trained scikit-learn Decision Tree classifier, an embedded persistent SQLite logging database layer, a 3-strike network counter, and a FastAPI schema are not looking for new code development, feature updates, or programming changes. The...

I have a list of online sources that contain both narrative text and numeric figures, and I need every one of those details captured in a single, well-structured Excel workbook. The job begins with careful data entry: copy each text field, metric, date, or code exactly as it appears on the web page and paste (or import) it into the template I will provide. Because the information is mixed data—words and numbers side by side—consistent formatting, proper column alignment, and vigilant error-checking are essential. Once the raw information is entered, the spreadsheet has to become an analysis tool. Please set up the formulas that calculate totals, averages, and any other basic statistics we agree on, then create clear charts or graphs that visualise the key results. Think of it ...

Data Collection & Extraction – Collect, extract, and organize data from multiple sources for analysis. Data Cleaning – Identify and remove duplicates, missing values, incorrect entries, and inconsistencies. Microsoft Excel – Handle large datasets using formulas, PivotTables, charts, sorting, filtering, conditional formatting, and data validation. Power BI – Create interactive dashboards and reports to visualize KPIs, trends, sales, inventory, and business performance. SQL – Query, filter, join, aggregate, and analyze data stored in relational databases. Python – Use Python for data analysis, automation, data manipulation, and reporting. NumPy & Pandas – Clean, transform, analyze, and manipulate structured datasets efficiently. Data Visualiz...

Intelligent Financial Fraud Detection System Python, SQL, XGBoost, Isolation Forest, SHAP, FastAPI, PostgreSQL, Streamlit, Docker, AWS Developed an end-to-end fraud detection pipeline processing financial transaction data using Python, SQL, and PostgreSQL, including data cleaning, exploratory analysis, feature engineering, and class-imbalance handling. Trained and compared Logistic Regression, Random Forest, XGBoost, and Isolation Forest models for supervised fraud classification and unsupervised anomaly detection. Engineered behavioral and transaction-velocity features including transaction frequency, amount deviation, new-device activity, unusual location, and time-based spending patterns. Implemented SHAP-based explainability to identify transaction-level factors contributing to fraud ...

I will provide a full export of my sales records and need a data analyst who can dive straight into the numbers, extract meaningful patterns, and translate them into recommendations the business can act on. The dataset includes fields such as product, region, channel, units, revenue, and date; if you discover gaps or outliers along the way, feel free to flag them so we can address them together. Your task is to explore the data statistically and visually, highlight the drivers behind revenue fluctuations, surface any seasonality or regional differences, and call out under-performing product lines. You are welcome to work in Python with pandas, NumPy, seaborn / matplotlib, or R and SQL—whatever makes the workflow efficient—as long as the final insights are presented in a clear,...