Data Science & Analytics
Statistical analysis, predictive modeling, and decision-grade dashboards — built by an engineer who treats your data as evidence, not vibes.
Who this is for
Operators, founders, and analytics leaders who need a defensible answer, not a notebook screenshot.
What problem this solves
Most 'data science' deliverables are notebooks the team can't re-run, charts no one trusts, and recommendations no one can defend. The work breaks the moment the data refreshes.
What you get
- A reproducible pipeline (Python or R) checked into your repo
- A statistical model with documented assumptions and confidence intervals
- A decision-grade report or dashboard your stakeholders can actually use
- A handoff session so your team can re-run and extend the work
How the engagement runs
- Discovery. We agree on the decision the analysis will inform — not just 'do data science'.
- Data audit. Schema review, quality checks, gap analysis. We tell you what's missing before we model.
- Modeling. Baseline model, then iteratively improve while documenting assumptions, residuals, and CIs.
- Communication. Report or dashboard with the headline answer up top, methodology in an appendix.
Deliverables
- Reproducible Python/R notebooks + scripts
- Trained model artifacts with version metadata
- Decision report (PDF + Markdown)
- Optional: Plotly/Streamlit/Recharts dashboard
- Handoff session (recorded)
Outcomes you can expect
- Clear yes/no/maybe answers your team can defend in a board meeting
- Time-series forecasts with documented MAPE / quantile intervals
- Cohort, funnel, and retention analyses re-runnable on every data refresh
Pricing & timeline
Single-question analyses $3K–$12K USD. Quarterly engagements $4K–$10K USD/month.
Single questions: 1–3 weeks. Ongoing analytics partnerships: monthly cadence.
Tech stack
- Python: pandas, NumPy, scikit-learn, statsmodels, Prophet, SciPy
- R: tidyverse, caret, forecast
- PostgreSQL, BigQuery, MongoDB, DuckDB
- Plotly, Recharts, Streamlit, Flask, Jupyter
- Apache Airflow for scheduled re-runs
Relevant case studies
- Indonesia Livestock Operations Dashboard — A real-time monitoring and intelligence dashboard for managing livestock supply chain operations across Indonesia's provinces.
- Enterprise Data Pipeline & Analytics Engine — A production-grade data engineering pipeline processing 10M+ records daily with automated ETL workflows, real-time analytics, and comprehensive business intelligence reporting.
- Statistical Analysis & Predictive Modeling Suite — A comprehensive statistical analysis platform combining Python and R for advanced analytics, predictive modeling, and automated report generation.
- Real-Time Analytics API with Flask & NoSQL — A high-performance Flask REST API for real-time event tracking and analytics, backed by MongoDB and Redis for sub-millisecond query responses.
Frequently asked questions about data science
- What makes you a 'best data scientist for hire' vs. a freelancer on Upwork?
- Two things: (1) every deliverable is reproducible code in your repo, not a one-off notebook, and (2) you're hiring an engineer who can also ship the dashboard or the model into production — not someone who hands off a PDF and disappears.
- Can you work with messy or partial data?
- Yes — we lead with a data audit and tell you what's recoverable before we touch a model. Most engagements include light data-engineering cleanup as part of the scope.
- Do you do A/B testing analysis?
- Yes. We've designed and analyzed experiments with multiple-comparisons correction, sequential testing, and Bayesian alternatives. We'll tell you when an experiment is conclusive — and when it isn't.
- What about forecasting?
- We've built ARIMA, Prophet, and ML-based forecasts at 92%+ accuracy for demand prediction. Every forecast comes with prediction intervals and a backtesting report.
- Can you teach my team while you're at it?
- Yes — we offer optional weekly 1-hour pairing or workshop sessions during the engagement. Cheaper than a separate trainer, and your team learns on real code.
- Do you handle GDPR / HIPAA-sensitive data?
- We sign DPAs, work inside your environment when required, and have shipped HIPAA-adjacent (US) and NHS Digital DSP-compliant (UK) systems. We do not pull PII to local machines without an explicit reason.