Data Scientist

Open position in RADaR office locations, including Kansas City, MO, Columbia, MO, and St. Louis, MO;
Hybrid work schedule: 3 days in the office, 2 days working from home

Visa sponsorship is not available for this position, now or in the future. Applicants must be legally authorized to work in the United States on a permanent basis without requiring employer sponsorship.

We’re seeking a Data Scientist with exceptional statistical expertise to join our team. In this role, you’ll work directly with advertising agencies and brands to analyze customer behavior patterns and advertising performance, developing sophisticated machine learning models that inform strategic marketing decisions.

• Conduct deep statistical analysis of customer behavior data and advertising performance metrics across multiple channels and campaigns
• Design, develop, and deploy machine learning models to predict customer responses, optimize advertising spend, and identify high‑value audience segments
• Perform advanced statistical modeling including regression analysis, hypothesis testing, time series analysis, and causal inference
• Build predictive models for customer lifetime value, churn prediction, attribution modeling, and campaign optimization
• Communicate complex analytical findings to both technical and non‑technical stakeholders through compelling data visualizations and presentations
• Develop automated reporting solutions and dashboards that enable clients to monitor campaign performance in real‑time
• Collaborate with cross‑functional teams to ensure data quality and integrity across all analytics initiatives
• Stay current with emerging techniques in data science, machine learning, and marketing analytics

• 3+ years of professional experience applying statistical methods and machine learning to business problems
• Strong foundation in statistical theory including probability, inference, experimental design, and multivariate analysis
• Demonstrated expertise in machine learning algorithms (e.g., random forests, gradient boosting, neural networks, clustering methods)
• Proficiency in Python or R for statistical analysis and machine learning, including libraries such as scikit‑learn, pandas, Num Py, stats models
• Experience with SQL and working with large‑scale databases
• Proven ability to design and analyze A/B tests and controlled experiments
• Track record of translating complex analytical insights into clear, actionable business recommendations
• Strong communication skills with the ability to present technical concepts to non‑technical audiences

• Experience working with advertising agencies, marketing teams, or in the ad tech industry
• Knowledge of digital advertising platforms (Google Ads, Facebook Ads, programmatic platforms)
• Familiarity with marketing attribution models and multi‑touch attribution methods
• Experience with cloud computing platforms (AWS, GCP, or Azure)
• Knowledge of causal inference methods and their application to marketing effectiveness
• Experience with customer data platforms (CDPs) and marketing automation tools

• Advanced degree (Master’s or Ph.D.) in Statistics, Mathematics, Computer Science, Economics, or related quantitative field

• The chance to be a part of a growing company and the next success story
• Amazing opportunities for career development
• Recognition programs
• Employee referral bonus
• Hybrid work schedule; 3 days in the office, 2 days working from home
• Fun and collaborative work environment
• Casual dress code
• Insurance Coverage (medical, dental, vision, life, and disability)
• 401(k) retirement plan, with employer 4% match
• Work/life benefits, including mental health and wellbeing support
• Flexible Time Off Policy
• Paid holidays, including agency closing Christmas Eve‑New Year’s Day
• Paid leave options, including sick leave, medical leave for self and family, and parental leave

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