Analysis

Reduce correlated variables to factors with PCA and varimax rotation

Fit nonlinear models to experimental data with scipy curve_fit

Test whether a time series shows a significant long-term trend

Build KPI frameworks, dashboards and predictive models for business analysis

Run statistical analysis, predictive models and data-driven business insights

Write fast Julia with multiple dispatch, performance tuning and numerical code

Navigate QuantDB parquet layouts, Hive partitions and symbol formats in DuckDB

Check QuantDB field units for volume, turnover, dividends and L2 tick data

Configure the QuantDB data SDK, API key and dataset queries

Fit dose-response curves and compute IC50, EC50 and Hill slope

Quantify microscopy images with morphometry, intensity stats and ANOVA

Convert lab instrument output into standard JSON and CSV for LIMS upload

Pool effect sizes with fixed or random effects, heterogeneity stats and forest plots

Run RNA-seq differential expression with DESeq2, edgeR and limma-voom

Fit regression, ANOVA, Cox survival and chi-square models with odds ratios and p-values

Write Excel formulas, pivot tables, charts and macros and clean messy data

Stress-test a finding across alternative analysis choices and report the spread

Run an R analysis pipeline from exploration and cleaning to regression tables

Compute statistical power, sample size and minimum detectable effect for a design

Build reproducible Monte Carlo studies reporting bias, RMSE, coverage and power

Build and run a Stata replication pipeline with logs, esttab tables and figures

Analyze datasets with statistical summaries, clear narratives and charts

Answer business data questions from a database using ktx semantic context

Structure EDA notebooks and analytics dashboards with sound section and chart choices

Build durable data catalogs with entity relationships and privacy citations

Track state, resumes and transitions for a data science engineering coach

Write feasibility studies that test whether your data supports an outcome

Generate synthetic datasets in a notebook after a safety preflight check

Analyze coding agent token use, cost and quota burn from ccusage usage data

Analyze Gemini conversation history from a Google Takeout export

Analyze text or files into facts, judgments and open questions

Diagnose a CSV time series for stationarity, seasonality, trend and forecastability

Create Fabric Activator alerts that notify you or act when values cross a threshold

Bring Azure Monitor and App Insights telemetry into Fabric Eventhouse for analysis

Answer business questions over Power BI reports and semantic models in plain language

Manage Fabric IQ ontologies with entity types, bindings and graph traversal

Audit and govern OneLake catalog health, labels, domains and item metadata

Find Fabric items by name across all workspaces and get their IDs

Analyze TikTok Shop video, live, affiliate and ad performance data

Run stateful, iterative Python in a live Jupyter kernel for data exploration

Gather weekly marketing numbers from tools and exports and clean them up

Join store revenue with ad spend to get true MER and new-customer cost

Analyze image, audio and video files and describe what they contain

Run parameterized Jupyter notebooks as batch report generators with papermill

Build publication tables like Table 1 and regression results in R or Python

Build reproducible Quarto reports and websites across R, Python and Julia

Create reproducible R Markdown analysis reports with knitr and bookdown

Filter, clean, sort and aggregate tables and time series data in MATLAB

Fit Weibull and life models to estimate MTTF and B10 life in MATLAB