Diagnostic Data Analyst Wanted

@Tanmoy236

Warm greetings! I’m an expert in data analysis and diagnostic analytics with 9+ years of experience using Excel, Python, Pandas, NumPy and Matplotlib. I’ll go beyond surface-level trends to identify root causes, anomalies and actionable business insights. Here's how I can help: * Exploratory analysis and data-quality checks in Excel * Deep diagnostic analysis using Python/Pandas * Statistical testing, anomaly and driver analysis * Clear visualizations and documented notebooks * Concise PDF/slide report with evidence and recommendations I’ll ensure the scripts run cleanly on your side. Could you share the dataset and key business questions to define the analysis plan?

@ShaikhAneesa

Hi there, I understand you need diagnostic analysis that goes beyond charts and summaries to identify the actual drivers behind your trends, anomalies and business questions. I’m confident I can combine Excel for rapid exploratory checks with Python/Pandas, NumPy and statistical analysis for deeper validation and root-cause investigation. My approach is to first profile and validate the dataset, define the agreed business questions, and identify data-quality issues, distributions, outliers and unexpected relationships. I’ll then drill into key segments and drivers, test relevant hypotheses, quantify the evidence behind the findings, and translate the results into practical recommendations. I’ll provide clean, documented Python notebooks/scripts, supporting Excel analysis, and a concise report or slide deck showing the findings, evidence and recommended actions. I’ve handled similar data-analysis and reporting workflows where the objective was to move from raw datasets and unexplained patterns to defensible, actionable insights rather than simply producing descriptive statistics. Could you share the dataset and the main business questions or anomalies you want investigated so I can define the initial diagnostic plan? I’m ready to start immediately. Warm Regards, Aneesa.

@WycOj

As a seasoned and versatile data analysis specialist, I utilize my expertise across several fields to deliver insights tailored to your specific needs. With over 7 years of experience in data science, medical and sales data analysis, your project aligns perfectly with my skill set. My knowledge of Python (Pandas and NumPy) and Excel for exploratory checks will ensure that we leave no stone unturned when rooting out the cause behind every trend and anomaly in your dataset. Moreover, my proficiency in languages such as R, SAS, SQL, and tools like Tableau is an added advantage not only for the success of our project but also for an enhanced engagement throughout. My analytical approach is always methodical and well-documented – two crucial factors needed for an impactful diagnostic analysis that results in actionable recommendations. Finally, I appreciate your workflow that ensures payment is dependent on the error-free running of the scripts on your end. This showcases a commitment not only to quality but to mutual satisfaction and it aligns with my professional values. I am dedicated to using my skillsets to extract the most meaningful insights from your dataset – transforming complex information into clear, practical recommendations you can act on immediately. Let's get started!

@usmanbashir12100

Hi, I can perform the diagnostic analysis using Excel for rapid exploration and Python with Pandas, NumPy, and Matplotlib for deeper investigation, focusing on identifying root causes rather than simply reporting trends. I’ll clean and document the analysis workflow, test anomalies against relevant variables, and deliver a concise evidence-based report with practical recommendations tied directly to the agreed business questions. A few questions: * What are the main trends, anomalies, or business questions you already suspect in the dataset? * Approximately how large is the dataset, and what are the key fields or data sources involved? * Do you have a preferred report format, such as PDF, PowerPoint, or Excel? Best regards, Muhammad Usman

@sareheshak

I can perform the diagnostic analysis using Excel for initial checks and Python (Pandas, NumPy, Matplotlib) for deeper analysis. I’ll identify trends, anomalies, and root causes, then provide clear recommendations supported by the data, along with clean code and a concise final report. 10+ years Advanced Excel experience, Certified Business Analytics, MBA. I can start by reviewing a sample dataset and your key business questions.

@belarjsoufiane20

Hi, I can help you uncover the root causes behind the trends and anomalies in your data. I have 7+ years of experience with Python, Pandas, statistical analysis, Excel, and data visualization. I’ll clean and analyze the data, identify the key drivers, and turn the findings into practical recommendations. You’ll receive clean Python code, Excel analysis, and a concise PDF report with the key insights. Send me the dataset and business questions, and I’ll get started.

@zafarfarooq612

Hello, I can perform a thorough diagnostic analysis using Excel for initial checks and Python/Pandas for deeper analysis, identifying trends, anomalies, and root causes. I’ll provide a clear analysis plan, well-documented code/notebooks, supporting Excel files, and a concise report with actionable recommendations. I’m detail-oriented and focused on producing accurate, practical insights that directly address your business questions. Regards, Zafar

@emanz03

The key is separating real business drivers from artifacts caused by missing values, outliers, joins, timing effects or inconsistent definitions. I’d first lock the business questions, audit the dataset in Excel/Pandas, then test segments, relationships and anomaly drivers before turning findings into a reproducible notebook and concise evidence-based report. I’d also include validation checks so your scripts rerun cleanly on the same data and produce the same conclusions.

@SakibKaiser

Hello, With an MSc in Data Science, Honours in Economics, and a 100% success rate across 30+ completed projects here, I specialize in diagnostic analysis. Having optimized UK energy grid capacities and authored strategic economic reports for the Oman government, I am fully equipped to translate your raw data anomalies into clear, error-free business recommendations. My Approach: Data Profiling (Excel/Pandas): Swift structural profiling to detect data-quality gaps, outliers, and systematic formatting errors. Root-Cause Modeling (Python): Deploying NumPy, Seaborn, and statistical correlation mapping to mathematically isolate the "why" behind your anomalies. Executive Delivery: Clean, fully commented Jupyter notebooks alongside an actionable, presentation-ready PDF report. Two brief questions for you: - Is there a specific anomaly (such as a sudden metrics drop or data discrepancy) that we should prioritize first? - What is the approximate size of the dataset, and are there multiple tables to join? Please share the dataset with me so I can run an initial diagnostic check and outline our next steps. Best regards, Shakib A.

@demivision

Hi there, Employer, Thank you for sharing your project – I appreciate how important it is to move from puzzling data to actionable insight. I understand you’re looking for a diagnostic data analyst who can not only spot trends and anomalies, but also explain the underlying causes in clear, business-focused terms. With expertise in Excel for rapid exploration and Python (Pandas, NumPy, Matplotlib) for deeper analysis, I’m confident I can help you get the clarity you need. In the past, I’ve partnered with organizations to unravel complex datasets—one recent example involved diagnosing unexpected sales fluctuations for a retail client, which led to targeted inventory and pricing changes that improved their bottom line. My approach always centers on combining rigorous analysis with practical recommendations, ensuring you have both the “what” and the “why” at your fingertips. Here’s how I’d approach your project: - Begin with a quick exploratory analysis in Excel to flag obvious trends, outliers, or data quality concerns. - Move into deeper exploratory and diagnostic analysis in Python, leveraging Pandas and NumPy for data manipulation, and Matplotlib/Seaborn for visualization. - Investigate root causes using correlation, segmentation, and hypothesis testing as appropriate. - Document all code and steps clearly, ensuring reproducibility and transparency. - Summarize findings in a concise report, highlighting key drivers behind the trends and providing practical, actionable recommendations. I’m comfortable with your workflow and payment approach, and I’m eager to help you turn your data into decisions. Looking forward to collaborating and tackling your data challenges together!

@ImranAli01

Hello, I got that you are looking for a seasoned data analyst to dive deep into your dataset using Excel and Python to uncover key trends and anomalies, providing practical recommendations based on the findings. This is what I can help you with, let's chat. My approach is to start with a thorough exploratory analysis in Excel to identify initial patterns, followed by utilizing Python with Pandas, NumPy, and Matplotlib for in-depth analysis. By applying advanced data analysis techniques, I will uncover the root causes behind the trends and anomalies, translating them into actionable insights for you. You can expect a detailed plan of the analytical approach, well-documented code/notebooks, and a concise report outlining key drivers, evidence, and suggested next steps. As final deliverables, you will receive a comprehensive analytical plan, cleaned code/notebooks, supporting Excel files, and a concise report detailing key findings and recommendations. One thing I'd like to confirm before we start: Do you have any specific business questions in mind that you would like the analysis to address? Looking forward to discussing further Best Regards, Imran

@Freelancersedo

Hello client, I can help uncover the key trends, anomalies, and underlying drivers in your dataset using Excel for initial exploration and Python for deeper analysis. I’ll provide clean, well-documented scripts, supporting Excel work, and a concise report explaining the evidence behind the findings and practical recommendations. I’m comfortable working from clearly defined business questions and can start by reviewing the dataset and preparing the analytical approach.

@MZITSERVICES

Hi, I can transform your raw data into accurate, meaningful, and publication-ready statistical results. I have strong experience with SPSS, Excel, R, Python, regression analysis, correlation, hypothesis testing, descriptive statistics, ANOVA, and data visualization. I will carefully clean and validate your dataset, select appropriate statistical methods, check assumptions, perform the analysis, and clearly interpret the findings. I can also provide organized tables, charts, statistical outputs, and a concise report aligned with your research objectives. Accuracy, reproducibility, and clear communication are my priorities. I’m ready to start immediately and deliver high-quality results within your deadline. Thanks ARM

@miguelcen64

Hello, The key part of this project is **identifying the real drivers behind the anomalies in your dataset and turning them into decisions you can act on immediately**. I can help you handle this accurately and efficiently without overcomplicating the process. I have hands-on experience with **Data Analysis, NumPy, and SPSS Statistics**, including exploratory diagnostics and cleaning messy datasets into clear findings. For your project, I would focus on **pattern and outlier detection**, **root-cause analysis of the strongest trends**, and **building a concise report with evidence-backed recommendations**, while making sure the final result is **easy to validate and ready to present**. I can start immediately and expect to complete this within 5 days. One detail I'd like to confirm before starting: **Which business questions should I prioritize first so the analysis stays tightly aligned with your decisions?** Best regards, Miguel

@Iwori

My approach to diagnostic data analysis focuses on isolating the exact variables driving anomalous patterns rather than just describing the surface metrics: 1. Data Audit & Triage: Quick exploratory profiling in Excel and Python to inspect distribution shifts, data integrity, and outlier clustering. 2. Root-Cause Decomposition: Using Pandas and NumPy for multi-dimensional segmentation, variance breakdown, cohort slicing, and statistical anomaly detection to isolate underlying drivers. 3. Actionable Synthesis: Translating statistical findings into an executive-ready deck/PDF with clear evidence and concrete next steps. In past diagnostic projects, I have investigated and resolved complex data discrepancies—such as isolating hidden operational bottlenecks skewing fulfillment metrics and segmenting user behavior to pinpoint the exact driver of sudden churn spikes. Deliverables: - Initial analytical plan aligned with your key business questions - Clean, thoroughly documented Jupyter Notebook/Python scripts (guaranteed to run error-free on your end) and supporting Excel files - Concise report highlighting core drivers, supporting data evidence, and actionable recommendations Ready to review the data once shared.

@robertb297

Hi, Diagnostic work usually breaks down when correlation gets mistaken for cause — before writing recommendations, I'll test whether a suspected driver actually explains the anomaly across different data cuts, not just where it first appeared. I've worked through similar root-cause investigations before, moving between Excel for quick checks and Python for deeper statistical dives on real-world datasets. My plan once you share the data: quick exploratory pass in Excel to spot obvious patterns, then a Python-based deep dive (segmentation, correlation checks, distribution analysis) to isolate root causes, followed by a concise report tying each finding to a specific recommendation. What are the 2-3 business questions you most want this to answer? That'll shape where I focus the diagnostic effort first.

@rimiloca

Hi, I can perform the diagnostic analysis in Excel and Python, identify anomalies and relationships, explain the likely causes, and provide reproducible charts and findings. I’ll first review the current setup and confirm access, edge cases, and the exact acceptance criteria. I’ll implement the change in a controlled way, preserve existing behaviour outside the agreed scope, and test the main user flows before delivery. You’ll receive a concise handoff explaining what changed, how it was verified, and anything that should be monitored after launch. I can also separate optional improvements from the required work so the estimate stays clear.

@abhay686

Hi, I have 7+ years of experience with data analytics, Python, Pandas, NumPy, Excel, SQL, data visualization, and root-cause analysis. I can start by understanding the business questions, then clean and validate the dataset, explore trends and anomalies, segment the data, test possible drivers, and identify the real reasons behind performance changes rather than only showing what changed. I have worked on operational, sales, KPI, and performance analysis where the focus was identifying gaps, bottlenecks, unusual patterns, and translating findings into practical business actions. You’ll receive clean Excel files, a fully documented Python notebook, supporting visualizations, and a concise PDF/slide report covering key drivers, evidence, recommendations, and next steps. I’ll also ensure the scripts run end-to-end before delivery. Let’s connect over the chat so that I can show you my previous work.

@imranahmadquresh

Hi, I understand you need Data Scientist using Python. I offer my services for this project. I hold the IBM Data Analyst Professional Certificate from IBM. I have made many Data Science based projects using Python as follows; • Predict Johnson & Johnson data using ARIMA & LSTM. • Stock Price Prediction of Amazon data & bank data using ARIMA & LSTM. • Handwritten Digit Recognition using Fourier response & SVM polynomial. • Classification of CIFAR-10 using different NN models. • Classification of London Fire Brigade incidents 2019-2022 data using Decision Tree. • Vehicle Classification using PCA, k-NN, Logistic regression, Decision tree, random forest, NN & CNN. • IOT Attacks Prediction using SVM, Decision Tree & Random Forest. • Prediction extent of disease of ECG data using Random Forest & SVM. • Time Series Price Forecasting using Random Forest. • Classification of dementia disease using XGboost & Logistics Regression. • Classification of Muffin & Cupcake ingredient data using SVM. • Classification of Nursery data using SVM & Logistic regression. • Prediction of Solar Radiance using SVM & Bayesian Ridge. • Regression of Boston & Diabetes using Decision Tree, NN & KNN. • Data analysis of 10 weather monitoring stations around Denver area. • Data analysis of Temperature & Rainfall of Washington, DC & Denver, CO. • Data analysis & Hypothesis Testing Hotel Booking Cancellation Prediction. I ensure to complete your project efficiently and on time.