Statystyka Jobs

I’ve collected raw accelerometer and gyroscope logs straight from an iPhone (CoreMotion CSV format) and now need a clear, well-documented statistical summary of that data. The goal is to understand central tendency, spread, correlation between axes, and any noticeable trends over time for both sensors. Please clean the dataset, handle missing or noisy readings, and then produce descriptive statistics (mean, median, variance, standard deviation, covariance), visualisations that highlight key insights (time-series plots, histograms, perhaps a correlation heat map), and a concise written interpretation of what the numbers show. I’m comfortable with Python, so a Jupyter Notebook built with pandas, NumPy, SciPy and Matplotlib or Seaborn is ideal. If you prefer R or MATLAB, that&...

I need my current inventory reviewed and recalibrated so that stock moves faster without creating service gaps. The focus is squarely on inventory management, specifically stock level optimization, with the primary success metric being a measurable improvement in stock-turnover rate. Here’s what the assignment involves: • Analyse recent SKU-level demand, lead times, and safety stock assumptions. • Calculate and recommend optimal reorder points / min-max levels that accelerate turnover yet still guard against stockouts. • Produce a clear implementation roadmap I can plug straight into our existing ERP or spreadsheet workflow, including any formulas, dashboards, or report templates you build. Please base all recommendations on easily auditable logic—if a ...

I have a raw dataset sitting in an Excel workbook and I need it turned into clear, decision-ready insights. The job is strictly data analysis—no macros or automated dashboards this time—so your focus will be on exploring the numbers, uncovering patterns, and presenting findings in a way that management can act on quickly. You are free to choose the most suitable Excel tools for the task: formulas, PivotTables, descriptive statistics, conditional formatting, or charts—whatever helps communicate the story behind the data most effectively. Deliverables • A copy of the original workbook, cleaned and structured for analysis • A separate analysis sheet (or set of sheets) that contains all calculations and visuals • A concise summary tab or short write-up ...

I am looking for a reliable and engaging online tutor to help my 11-year-old daughter with Mathematics and Science. She is currently in Grade 6 and needs support to strengthen her fundamentals and concepts. Schedule & Commitment: • Frequency: 5 days a week. • Format: Two 45-minute sessions daily (one for Maths, one for Science). Budget: INR 2,000 per month (Fixed Price).

I need our raw financial numbers transformed into clear, interactive Power BI reports that management can rely on for day-to-day decisions. The datasets live in SQL Server plus a few recurring Excel exports; once connected, they must be modelled, cleaned, and enriched with the right DAX measures before being published to Power BI Service and shared through workspaces. What matters most to me is your experience: show me a brief overview of similar finance or accounting projects you’ve handled, the size or complexity of the data involved, and any notable outcomes you helped your client achieve. Screenshots or live demo links are welcome if you can share them. Deliverables I expect: • Robust data model with refresh schedules configured • A suite of role-based reports (P&...

I am in the middle of my MSc thesis in machine learning and the central hurdle is implementing and fine-tuning both Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) on a proprietary “Bank Data of accounting ratios” dataset. I already have a draft data pipeline and preliminary feature engineering in place, but I need an experienced collaborator who can turn these models into publishable-quality work and guide me in framing the statistical narrative behind them. Beyond the deep-learning core, the study compares the neural results against classic ensemble methods—XGBoost, bagging—and a baseline logistic-regression model. A solid command of statistics is therefore essential to validate assumptions, check multicollinearity, and report confidence...

I need a skilled data scientist to train and validate AI models using historical household energy consumption data. The primary goal is to detect anomalies in the data. Key Requirements: - Train AI models (regression, classification, or time-series) - Validate models for accuracy and reliability - Use historical energy consumption data Ideal Skills and Experience: - Expertise in machine learning and AI - Strong background in data analysis and statistics - Experience with energy consumption datasets - Proficiency in programming languages like Python or R - Ability to deliver clear, actionable insights from the models Please provide examples of similar work and your approach to the project.

I have a raw dataset sitting in an Excel workbook and I need it turned into clear, decision-ready insights. The job is strictly data analysis—no macros or automated dashboards this time—so your focus will be on exploring the numbers, uncovering patterns, and presenting findings in a way that management can act on quickly. You are free to choose the most suitable Excel tools for the task: formulas, PivotTables, descriptive statistics, conditional formatting, or charts—whatever helps communicate the story behind the data most effectively. Deliverables • A copy of the original workbook, cleaned and structured for analysis • A separate analysis sheet (or set of sheets) that contains all calculations and visuals • A concise summary tab or short write-up ...

I have a raw dataset sitting in an Excel workbook and I need it turned into clear, decision-ready insights. The job is strictly data analysis—no macros or automated dashboards this time—so your focus will be on exploring the numbers, uncovering patterns, and presenting findings in a way that management can act on quickly. You are free to choose the most suitable Excel tools for the task: formulas, PivotTables, descriptive statistics, conditional formatting, or charts—whatever helps communicate the story behind the data most effectively. Deliverables • A copy of the original workbook, cleaned and structured for analysis • A separate analysis sheet (or set of sheets) that contains all calculations and visuals • A concise summary tab or short write-up ...

I'm seeking an experienced professional in Python, specifically with expertise in simulated annealing. This is for a master's project. Requirements: - Proficiency in Python - Strong understanding of simulated annealing - Experience in optimization problems Ideal Skills: - Background in algorithms - Experience with heuristics and metaheuristics - Ability to provide insights and guidance for a master's level project Please include relevant experience in your application.

I’m running a study and need a reliable partner to source and organise the raw data that will feed my analysis. The subject matter and variables are ready; what’s missing is the actual dataset. Here’s what I need from you: • Locate and collect the specified records exactly as outlined in the brief I’ll share after kickoff. • Validate the information for accuracy and completeness, flagging any gaps or anomalies. • Deliver the cleaned dataset together with a short log of your methodology and sources so the work is fully replicable. I’m comfortable receiving the final file in whichever structure you prefer—Excel, CSV, or a lightweight database—as long as it’s clearly labelled and ready for statistical processing. I’m o...

I have a sizable financial dataset that I need transformed into clear, actionable insights. Your main focus will be running descriptive statistics on the raw numbers, then weaving those results into an interactive dashboard that decision-makers can explore at a glance. To get there, you’ll work heavily with VLOOKUP/HLOOKUP for quick cross-sheet lookups, build concise pivot tables, craft eye-catching charts, and use slicers or timelines so the final workbook feels intuitive, not intimidating. Accuracy matters—totals must reconcile and every formula has to handle new data drops without breaking. Deliverables • A clean, well-structured workbook containing the original data, helper columns, and all formulas • Pivot tables summarizing key financial metrics with desc...

I need a complete, publish-ready dissertation of roughly 60 pages (about 15,000 words) in the field of Finance, specifically centred on an Investment Analysis question you help me refine. The paper must follow standard academic structure—abstract, introduction, literature review, methodology, results, discussion, conclusion, references—formatted to APA 7. Data work is critical: the methodology section should feature an econometric study executed in EViews (Gretl is fine for secondary checks). I will supply either a raw data set or guidance on the database to extract from; you will clean, model, and interpret it, then insert all relevant tables, graphs, and code appendices into the text. Timing is tight, so I’ll need the whole draft quickly, with two interim checkpoints ...

I have two computer-science courses with about twenty students each. Every assignment mixes multiple-choice items, fill-in-the-blank questions, and a handful of very short Python snippets. I will supply a complete answer key in Jupyter (.ipynb) notebooks together with the students’ submissions (also .ipynbs). Your task is to score each response, record the points I specify for every question, and add concise feedback where it will help the student improve(eg. a few notes for each student who misses problems, but they all usually do well). When you reach the coding parts I need a careful read-through—run the cell if you like—to be sure they actually understand the material and haven’t pasted AI output. I'll send over a a spreadsheet to input the scores for e...

I want to launch a web-based economic trend-forecasting tool that zeroes in on the Indonesian Rupiah, US Dollar, and Malaysian Ringgit. The goal is to let me visualise historical movements, overlay key macro-economic indicators, and generate forward-looking projections I can download or embed in reports. Here’s what I’m after: • A clean browser interface that loads quickly on desktop and mobile, with interactive charts for each currency and the pairs IDR-USD, MYR-USD, and IDR-MYR. • A data layer that automatically pulls reliable, up-to-date market prices and macro metrics (think API feeds such as Alpha Vantage, FRED, or similar—open to your suggestions). • A forecasting engine that applies recognised statistical or machine-learning methods to surface ...

I'm seeking an experienced statistician to assist with a health sciences research project. The project involves analyzing retrospective data using binomial logistic regression analysis. I want it to be incremental. I will have my IRB approved soon. Thereafter, I will pull data on admissions characteristics, in program characteristics and see how it correlates to a pass/fail on licensure exam. Key requirements include: - Expertise in regression analysis - Experience with health sciences research - Proficiency in handling and analyzing retrospective data - Strong background in statistical software (SPSS) Ideal candidates will have a background in health sciences and a proven track record of successful data analysis in academic research.

Îmi pregătesc un articol bazat pe cercetare proprie și am nevoie de ajutor pentru a integra și interpreta datele clinice împreună cu analize statistice riguroase, astfel încât materialul final să fie relevant și convingător pentru profesioniștii din domeniul medical. Vei primi seturile brute de date clinice (variabile demografice, evoluția unor markeri biologici și scoruri de severitate) și un rezumat al design-ului de studiu. Sarcina ta este să: • curăți și structurezi baza de date; • aplici testele statistice adecvate (probabil va fi nevoie de teste t, ANOVA, regresii logistice și analize de supraviețuire); • generezi grafice clare și tabele publicabile conform standardelor jurnalelor biomedicale (format APA sau Vancouver); • redactezi ...

This is a highly challenging, research-level task that requires strong expertise in chemical engineering and advanced process simulation, particularly Aspen Plus and Aspen Custom Modeler (ACM). The project involves replicating the following paper fully in (Aspen Custom Modeler Only): Joel et al. (2017) – Modelling, simulation and analysis of intensified regenerator (CO₂ stripper) for solvent-based carbon capture using rotating packed bed (RPB) technology Paper link (also attached to this project for direct download): The original model was implemented using Aspen Plus FORTRAN subroutines. The goal is to rebuild the RPB CO₂ stripper model natively in ACM, validate it using Cheng et al. pilot-plant data, and document the full modeling procedure. Scope (Summary) Develop a comple...

For the next six weeks (Monday – Thursday, two hours per day) I’m running an intensive online up-skilling program for a 12-15 employees. The group have moderate Excel experience and material must strike a balance between reinforcing fundamentals and diving into expert-level techniques. Content scope • Power BI Desktop interface, data sources, visualizations • Sample dashboard featuring the Animation Visual • AI visuals and other advanced visualization options • Query Editor, data modeling, and performance tuning • Data shaping, custom transformations, and optimization strategies • DAX: from core concepts to advanced patterns • Live database connections and incremental refresh • Power BI Service, workspace governance, secu...

I have several retrospective ICU studies underway and I need an analyst who already feels at home inside both MIMIC-III and MIMIC-IV on PhysioNet. The work centres on pulling raw tables, stitching them together through patient and hospital-stay identifiers, and transforming that sprawl into tidy, analysis-ready cohorts. Every step—from initial SQL queries to the last model diagnostic—must be reproducible and clinically defensible. Day to day you will: • Extract rows from the core Meds, diagnoses, procedures, labs, and vitals tables, then link them reliably across encounters. • Clean and preprocess the high-dimensional data, flagging implausible values and resolving unit or time-stamp issues. • Derive clinically meaningful variables (severity scores, medica...

Busco un/a especialista en Power BI para el desarrollo de dashboards interactivos, modelado de datos y generación de indicadores (KPIs). El proyecto requiere experiencia en visualización de datos, análisis y presentación de información para apoyo a la toma de decisiones. Requisitos: Power BI (avanzado) Modelado de datos y DAX Creación de dashboards interactivos Análisis de datos y KPIs Integración de datos desde múltiples fuentes (APIs, bases de datos, archivos) Se valorará: Experiencia en proyectos de análisis social o tecnológico Buen criterio visual y claridad en reportes Cumplimiento de plazos y comunicación constante INDISPENSABLE QUE HABLE ESPAŃOL Y SEA DE AMÉRICA LATINA, POR ...

I have already drafted a paper titled “Deep Intelligence and IoT-based Framework for Precise Yield Estimation and Management of Agricultural Crops.” What I now need is a full survey/review article—polished to SCI-journal standards—that zeroes in exclusively on yield estimation methods. Your task is to build on my draft and broaden it into a state-of-the-art overview. The narrative should map out the theoretical foundations of every prominent yield estimation approach, from traditional statistical models and machine-learning regressors to cutting-edge deep learning, computer-vision, remote-sensing, and sensor-fusion techniques. I want a rigorous, side-by-side comparison that highlights assumptions, data requirements, accuracy metrics, and computational complexity; t...

I have several sets of structured data in spreadsheets and simple database exports that I need transformed into a clear, insight-rich summary. The work centres on cleaning the files, running descriptive statistics, creating intuitive visuals, and assembling a concise narrative that highlights the most important findings. You’ll receive the raw CSVs and a small MySQL dump. Feel free to work in Python (pandas, matplotlib, seaborn), SQL, Excel, or any comparable stack you prefer—as long as the workflow is reproducible and I can rerun it later if the data updates. Deliverables • A cleaned, well-documented dataset • A short written report (PDF or slide deck) that explains trends, aggregates, and any unexpected patterns in plain language • Visualisations and/or...

I will complete a series of interviews with recent immigrants and then need to turn those conversations into an 8- to 10-page research paper that reads like an academic study. The paper must centre on three interrelated resource areas—Employment opportunities, Housing and accommodation, and Access to healthcare—showing how my respondents experience each one and where the biggest gaps lie. All transcripts, observation notes, and demographic tables will be shared with you. What I need is a clear roadmap for shaping that material into a cohesive paper: advice on tightening the research question, a logical section order, and help choosing the right analytical lens. Once the structure is settled, I’d like hands-on support drafting the most demanding parts of the manuscript&md...

I need to analyze monthly sales trends using Power BI. Key Requirements: - Create interactive and insightful Power BI dashboards - Analyze monthly sales trends - Use existing Excel data sources Ideal Skills and Experience: - Expertise in Power BI - Strong background in sales data analysis - Proficient in Excel data integration

This project delivers an intelligent Employee Promotion Prediction system built using machine learning techniques to support data-driven and unbiased HR decisions. The system analyzes multiple employee attributes, including performance ratings, years of experience, training history, and key behavioral indicators, to predict promotion eligibility with high accuracy. What sets this project apart is its end-to-end approach: starting from data preprocessing and feature engineering, through model selection and evaluation, to interpreting results in a way that is meaningful for HR stakeholders. Rather than relying on subjective judgment alone, the model provides objective insights that help identify high-potential employees early and consistently. The project emphasizes fairness, transparency,...

This project delivers an intelligent Employee Promotion Prediction system built using machine learning techniques to support data-driven and unbiased HR decisions. The system analyzes multiple employee attributes, including performance ratings, years of experience, training history, and key behavioral indicators, to predict promotion eligibility with high accuracy. What sets this project apart is its end-to-end approach: starting from data preprocessing and feature engineering, through model selection and evaluation, to interpreting results in a way that is meaningful for HR stakeholders. Rather than relying on subjective judgment alone, the model provides objective insights that help identify high-potential employees early and consistently. The project emphasizes fairness, transparency,...

I have a clean dataset of 250 subjects ready for a full biostatistical work-up. My primary goal is to assess incidence rates, then dig deeper into how those rates vary across key demographics—specifically Age and Gender. Here is the scope I need covered: • Descriptive summaries of the sample’s age and gender profile. • Incidence calculations with confidence intervals. • Chi-square tests (or Fisher’s where counts are small) to compare categorical outcomes across age strata and between males and females. • Mann-Whitney tests for any non-parametric continuous comparisons I flag during the hand-over. • Logistic regression models to explore associations between selected predictors and the outcome, including an age-group subgroup analysis. ...

1- Task is to visit an institute physically and take atleast 10-15 geotagged photos of the name board of the institutes captured from outside the building and preferably inside too. Download app for geotagged pics from the link: 2- Get the verification forms filled, signed and stamped by the HR or relevant authority of these locations. 3- Get the details of verifier that is their name, designation, Department and Contact. 4- In case of refusal to fill form, take the written refusal statement with stamp or sign as a proof. If they don't give written, ask them that you want to record them saying their reason and take their details like name designation contact etc. If both isn't possible, just take their details like name of person whom you met, their designation, contact, or t...

I have a raw dataset sitting in an Excel workbook and I need it turned into clear, decision-ready insights. The job is strictly data analysis—no macros or automated dashboards this time—so your focus will be on exploring the numbers, uncovering patterns, and presenting findings in a way that management can act on quickly. You are free to choose the most suitable Excel tools for the task: formulas, PivotTables, descriptive statistics, conditional formatting, or charts—whatever helps communicate the story behind the data most effectively. Deliverables • A copy of the original workbook, cleaned and structured for analysis • A separate analysis sheet (or set of sheets) that contains all calculations and visuals • A concise summary tab or short write-up ...

I have a raw dataset sitting in an Excel workbook and I need it turned into clear, decision-ready insights. The job is strictly data analysis—no macros or automated dashboards this time—so your focus will be on exploring the numbers, uncovering patterns, and presenting findings in a way that management can act on quickly. You are free to choose the most suitable Excel tools for the task: formulas, PivotTables, descriptive statistics, conditional formatting, or charts—whatever helps communicate the story behind the data most effectively. Deliverables • A copy of the original workbook, cleaned and structured for analysis • A separate analysis sheet (or set of sheets) that contains all calculations and visuals • A concise summary tab or short write-up ...

Title: ML Expert Required for Advanced Trading System (Hybrid ML–RL) Description: We are looking for an experienced Machine Learning expert to work on an advanced algorithmic trading module. Requirements: Strong expertise in Machine Learning / Reinforcement Learning Hands-on experience in trading systems (stocks, futures, or options) Ability to design and optimize ML-based trading models Practical understanding of market data and execution logic Note: Only ML experts with trading module experience should apply. No other roles are required.

I’m looking for a data-savvy partner who can turn a raw set of finance-sector customer transaction data into clear, insightful storylines. My priority is descriptive analysis: I want to understand what has happened—patterns in spending, seasonal spikes, product uptake, and any anomalies that jump off the page. Here’s what I’ll hand over: • Raw customer transaction files (CSV/Excel). • A brief explaining column meanings, business context, and any compliance notes. Here’s what I’d like back: • A cleaned, well-documented dataset ready for future work. • An exploratory data analysis notebook or script (Python, R, or SQL) with comments so I can reproduce every step. • A concise slide deck or PDF report highlighting key metrics...

I need support turning several raw transactional and user-behaviour datasets into clear, decision-ready insights for an upcoming strategy review. The work is fully freelance and centers on data analysis, so skills in Python (pandas, NumPy, scikit-learn), R, SQL, or a comparable stack are essential. Expect to begin with cleaning and normalising PostgreSQL and CSV data, move on to exploratory and statistical analysis, and finish with a concise report and visualisations that non-technical stakeholders can understand. A lightweight Power BI or Tableau dashboard would be an appreciated bonus if it helps stakeholders drill deeper on their own. Deliverables • Re-run-able, well-annotated scripts or notebooks • A short methodology note explaining assumptions and modelling choic...

We are seeking an experienced professional to develop mathematical models and Random Number Generator (RNG) systems for a casino game. The project will involve creating robust mathematical algorithms to ensure fair gameplay and designing RNG systems that meet industry standards. The ideal candidate should have expertise in game theory, probability, and statistical modeling, as well as experience in developing secure and provably fair RNG systems. Strong attention to detail and confidentiality is a must.

I need assistance with running statistical analyses on survey data for my dissertation using SPSS. Key Requirements: - Conduct statistical analysis using SPSS - Analyze survey data - Provide detailed interpretation of results Ideal Skills and Experience: - Proficiency in SPSS - Strong background in statistical analysis - Experience with survey data Looking for someone with a strong analytical background and experience in academic research.

Here is the same conten This report focuses on Predictive and/or Prescriptive Data Analysis using machine learning techniques. The objective is to demonstrate the ability to use analytical tools to build predictive models based on a chosen dataset within a specific industry or enterprise context. The analysis should identify opportunities for growth, potential threats, and hidden data patterns that can support leadership decision-making. Purpose The purpose of this report is to evaluate the ability to: Apply analytical tools effectively Build and evaluate predictive or prescriptive models using machine learning Interpret results within a real industry or business context Identify opportunities, risks, and hidden patterns Support leadership decision-making through data-driven insights The ...

I need a mathematician or quantitative analyst to validate financial risk assessment models. Key Tasks: - Verify the accuracy of existing risk models - Ensure all computations and algorithms are correct - Check data consistency and integrity - Provide a detailed report on findings Ideal Skills and Experience: - Strong background in finance and risk management - Expertise in statistical analysis and algorithm verification - Familiarity with financial models and quantitative methods - Experience in providing validation reports -people who understand financial mathematics, AMMs (automated market makers), prediction markets, and risk modeling.

I am interested in developing an econometric model for my thesis. If, after my advisor’s review, everything is approved and considered appropriate, that would be perfect. In case modifications are required, ideally they should remain within the agreed budget. Once the model is completed, I would like to receive a full explanation of it, including how it is developed and the necessary knowledge to be able to replicate it in the future. If this explanation involves an additional cost, I would appreciate knowing the price both with and without this component. Required information: The thesis focuses on the Venezuelan diaspora and its effects on economic variables. The variables to be used in the econometric model include GDP, migration rate, and remittances. Alternatively, in the Exc...

I need a Python-based agent that continuously gathers real-time data on Caribbean economies and sectors, then turns those streams into clear, decision-ready market briefs. The agent must: • Pull data asynchronously from at least five live sources—specifically Financial APIs, News services, and Economic databases—while retrying intelligently so data freshness is never compromised. • Store, structure, and time-stamp each datapoint for reproducibility. • Run statistical trend analysis (e.g., moving averages, YoY deltas, volatility) and generate regional comparisons across Caribbean countries. • Pass the processed insights to Claude AI and receive executive-level narratives that highlight key movements, risks, and actionable recommendations. • Pa...

I have a multi-sheet Excel model that projects our revenue, expenses and cash-flow for the next three years. Somewhere along the way formulas broke, links between tabs went missing, and totals no longer tie out. I need a sharp Excel specialist who can jump in right away, diagnose every inconsistency, and hand the workbook back in clean, error-free shape. What I’m expecting once you’re done: • All formulas, references and links repaired or rebuilt • A quick audit sheet that flags the key drivers and lets me tweak assumptions easily • Reconciled summary totals so revenue, expenses and cash-flow match across every tab • Basic checks (circular-reference warnings off, no #REF! or #DIV/0!) to keep the file stable The file is ready to share immediately and ...

I’m preparing an acquisition for a private-equity backed roll-up and need a robust, M&A-style model built from the ground up. The focus is on deal structuring: I want to see how different mixes of debt, seller rollover, management equity and carried interest flow through a full LBO model and ultimately shape the post-close cap table. Here’s what I’m after: • A dynamic Excel (or Google Sheets) workbook that starts with purchase price, sources & uses and flows through the standard LBO drivers—revenue build, operating assumptions, debt schedule, interest, tax shield, working capital and exit. • An integrated capitalization table that automatically updates from the assumptions tab, shows every security class at close and at exit, and highlights dil...

I need a clear, data-driven assessment of several cryptocurrency assets before I commit new capital. The work centres on investment analysis, not general market commentary, so every conclusion must be backed by numbers I can trace. Here’s what I need from you: • A comparative valuation of the coins and tokens I list, using recognised metrics such as on-chain activity, network value-to-transactions, and discounted cash-flow proxies where relevant. • Scenario-based forecasts that show best, base, and worst-case returns over the next 6–12 months, with assumptions stated explicitly. • A risk profile covering volatility, liquidity, counter-party exposure, and regulatory considerations, supported by Value-at-Risk or similar models. • An actionable summ...

I'm looking for a skilled data analyst to perform survival analysis in the healthcare domain. The data will be synthetic, as real data cannot be used. Key Tasks: - teach me survival analysis, cox regression and logistic regression Ideal Skills and Experience: - Expertise in survival analysis techniques. - Proficiency in statistical software (SPSS or R). - Background in healthcare data interpretation. - Strong analytical and problem-solving skills.

I need a complete Python workflow that forecasts the likelihood of road accidents under different conditions. I will be working in PyCharm and expect the code to rely on Scikit-learn for the classical algorithms and XGBoost for gradient boosting, with Seaborn for exploratory visuals. Data strategy • Accident records: start with reputable, publicly available crash datasets. • Weather: scrape real-time and historical conditions so each accident row carries temperature, rain, visibility, etc. • Traffic: enrich the set with crowdsourced density figures (e.g., Waze, TomTom, or similar feeds). Core tasks 1. Clean and merge the three data streams, handling missing values responsibly. 2. Engineer features around time of day, road type, weather categories, and traffic c...

I have a production database full of raw numerical records that first need to be cleaned and processed before any modelling work can begin. The task centres on building a repeatable Python pipeline that pulls the data directly from the database, applies rigorous quality checks, and outputs a tidy, analysis-ready table. I expect the script to connect via SQL (SQLAlchemy or similar), ingest the relevant tables, and then handle missing values, outliers, type casting, and duplicate detection. Once cleaned, the data should be written back to a new table in the same database and optionally exported to CSV so that downstream teams can verify the results in Excel if they choose. Key deliverables – Python script (Pandas, NumPy, SQLAlchemy preferred) that performs the full ETL/cleaning...

Seasoned, data-driven insight into upcoming stock market movements is the core of this assignment. I want a professional trader’s market analysis focused exclusively on listed equities, with the clear objective of predicting short-, mid- and long-term trends so I can time future entries and exits more confidently. The work should go beyond headline commentary; I need a structured, evidence-based narrative that pulls from solid technical and fundamental indicators, macro-economic context and order-flow sentiment. Feel free to lean on whatever you normally rely on—Bloomberg Terminal, TradingView, Python back-tests, Excel models, proprietary screeners—so long as the methodology is transparent and reproducible. Deliverables • A concise written report (PDF or Google Doc...

I have a data-processing initiative that is still taking shape, and I’m looking for a freelancer who can help me turn my raw information into meaningful, reliable output. Because the scope is open, we can decide together which data types to tackle first and the best workflow to apply—whether that means pulling text from documents, crunching numbers from spreadsheets, or preparing imagery for later analysis. Your role will involve setting up a clean, repeatable pipeline, running a few test batches with sample data I provide, documenting each step clearly, and leaving me with scripts or templates I can maintain on my own. I’m happy to work with popular tools such as Python, SQL, or even Excel if you believe they’re the right fit, and I welcome alternative suggestio...

My customer records live in several Excel workbooks and I need more than simple data input—I need data analysis focused on customer metrics. The job centers on Customer data analysis, not data cleaning or generic data entry. I’ll supply the raw spreadsheets; your task is to turn them into an insightful workbook that highlights patterns, opportunities, and risks hidden in the numbers. Here’s what I’m after: • A well-structured Excel file where raw tables are cleaned, linked, and ready for exploration (Power Query or formulas—whichever suits the data best). • Pivot tables, charts, or dashboards that surface actionable customer-focused insights—think behavior indicators, cohort trends, or any other angle you feel reveals value. • A conci...

I have a time-sensitive retail analytics assignment that has to be wrapped up within 3 to 4 days. Once we start, I’ll share the raw transactional files and a short requirements brief. You’ll first wrangle the data in SQL , then move into Python for any advanced calculations or feature engineering, and finally present the insights in an interactive Power BI dashboard. Core focus • Clean and model the data so that it is query-ready • Produce a concise Python notebook that documents every transformation • Build a visually polished Power BI report with slicers, drill-downs, and KPI cards Acceptance criteria 1. SQL scripts execute without errors on my side. 2. Python notebook runs end-to-end via a single “Run All” and outputs the final dataset....