GTM Data Scientist: Growth & Retention Analytics

Spectrum Equity; Lindon (UT); On-site; USD 95,000 - 125,000; Full time

Job summary

Awardco in Lindon, Utah is seeking a Data Scientist to partner with Go-to-Market (GTM) teams to influence customer acquisition, retention, and expansion through causal inference and predictive modeling.

You'll build models such as health/churn scores, expansion likelihood, and lead scoring, design and analyze experiments (A/B tests), and collaborate with Marketing, Sales, Revenue Operations, and Customer Success using Python, SQL, and Snowflake.

Qualifications

• Bachelor's or Master's degree in Statistics, CS, Economics, Data Science, or another quantitative field.
• 3–5 years of applied data science experience.
• Strong Python proficiency and libraries (pandas, scikit-learn, statsmodels).
• Experience with designing/analyzing A/B tests and causal inference methods.

Responsibilities

• Partner with GTM stakeholders across Marketing, Sales, Revenue Ops, and Customer Success.
• Design, run, and analyze experiments (A/B tests) and causal-inference methods.
• Build predictive models (health/churn, expansion likelihood, LTV, lead scoring).
• Collaborate with BI/Data Engineering on metrics and data infra.
• Work with Python and SQL against Snowflake to build analytics/ML infra.

Skills

Python proficiency

SQL

A/B testing

Causal inference

Data visualization

Machine learning

Non-technical stakeholder engagement

Exploratory analytics

Education

Bachelor's or Master's in a quantitative field

Tools

Snowflake

Databricks ML

Airflow

Looker/Tableau/Plotly

Job description

Awardco in Lindon, Utah is seeking a Data Scientist to partner with Go-to-Market (GTM) teams to influence customer acquisition, retention, and expansion through causal inference and predictive modeling.

You'll build models such as health/churn scores, expansion likelihood, and lead scoring, design and analyze experiments (A/B tests), and collaborate with Marketing, Sales, Revenue Operations, and Customer Success using Python, SQL, and Snowflake.