> Markdown version of [/jobs/ext/3843693-senior-data-scientist](https://www.wearedevelopers.com/jobs/ext/3843693-senior-data-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Senior Data Scientist

- **Company:** Tiger Analytics
- **Location:** St. Louis, MO, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Business Analytics Applications, Data Analysis, Big Data, Information Engineering, Data Mining, Python (Programming Language), Machine Learning, SQL Databases, Deep Learning, Model Validation, AutoML
- **Published:** October 20, 2026
- **Apply:** https://www.juju.com/job/16_57f1aad44

## About the Role

* 8 years of experience in data science and ML models
 * Hands-on expertise in Python and SQL for data analysis and modelling.
 * In-depth experience with A/B testing or similar methodologies such as Causal ML, Matching Models, or Auto ML.
 * Strong problem-solving skills with the ability to work independently on end-to-end data science projects.
 * Excellent communication skills and stakeholder management experience.
 * Solid understanding of regression, classification, and statistical methods

## Description

As a Data Scientist you will be at the forefront of solving high-impact business problems using advanced machine learning, data engineering, and analytics solutions. The role demands a balanced mix of technical expertise, stakeholder management. You will design and analyze A/B tests and apply advanced techniques such as causal inference, matching models, and AutoML to generate reliable, actionable insights. Partnering closely with business and cross-functional teams, you will translate hypotheses into robust analytical models, validate outcomes with statistical rigor, and clearly communicate results to drive data-backed decision-making and measurable business value., * Apply statistical techniques and machine learning methods to solve complex business problems.

 * Build, validate, and deploy predictive and analytical models using Python.
 * Perform data extraction, transformation, and analysis using SQL across large datasets.
 * Work on causal inference techniques such as causal ML, matching models, or uplift modeling to evaluate business interventions.
 * Collaborate with product, business, and engineering teams to translate requirements into scalable data solutions.
 * Present insights, findings, and recommendations clearly to technical and non-technical stakeholders.
 * Ensure data quality, model performance, and continuous improvement of analytical workflows.