Analytics & BI

Data Science Consulting

Not every analytics problem needs a machine learning model. Sometimes the right tool is a well-designed experiment, a statistical test, or a carefully built simulation. We bring rigorous analytical thinking to business problems and recommend the simplest approach that gives a reliable answer.

15+

Data Scientists on Team

100+

Analytical Projects Completed

6 Weeks

Avg Engagement Duration

What We Deliver

Data Science Consulting Services

Practical, production-ready work — not proofs of concept that never make it to real users.

Exploratory Analysis

Deep-dive analysis on specific business questions to understand what the data shows, what it doesn't, and what additional data is needed.

Experimentation Design

A/B test and multivariate experiment design with proper power calculations, randomization, and guardrail metrics.

Causal Inference

Quasi-experimental methods including difference-in-differences and instrumental variables for situations where randomization is not possible.

Analytical Modeling

Statistical and simulation models for pricing optimization, resource allocation, and scenario planning.

How We Engage

Common Engagements

01

Pricing Analysis

Statistical analysis of price elasticity and competitive positioning to inform a pricing strategy change.

02

Marketing Mix Modeling

Attribution model that quantifies the incremental contribution of each marketing channel to revenue.

03

Feature Impact Analysis

Causal analysis of whether a product feature change actually drove the metric improvement or just correlated with it.

04

Operational Simulation

Simulation model to test staffing and capacity decisions under different demand scenarios before committing resources.

Why InnovTen

What You Can Count On

  • Rigorous statistical methods that avoid common analytical pitfalls like p-hacking and confounding
  • Plain-language communication of findings to non-technical stakeholders
  • Code and documentation delivered so your team can replicate and extend the analysis
  • Honest assessment of what the data can and cannot tell you
  • Recommendations grounded in what is statistically defensible, not what looks good in a slide

Technologies We Use

Python R SQL Statsmodels Scipy Stan Jupyter dbt Snowflake BigQuery

Ready to Get Started?

Tell us about your project and we'll put together a practical path forward.

Talk to Our Team