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.

Essential Duties and Responsibilities (Other duties may be assigned)

• 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

Qualifications - To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• 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, NumPy, statsmodels
• 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

Preferred Qualifications:

• 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

Education

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

Total Perks Package

• 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 soft closing Christmas Eve-New Year's Day
• Paid leave options, including sick leave, medical leave for self and family, and parental leave

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.

Essential Duties and Responsibilities (Other duties may be assigned)

• 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

Qualifications - To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• 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, NumPy, statsmodels
• 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

Preferred Qualifications:

• 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

Education

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

Total Perks Package

• 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 soft closing Christmas Eve-New Year's Day
• Paid leave options, including sick leave, medical leave for self and family, and parental leave

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.

Essential Duties and Responsibilities (Other duties may be assigned)

• 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

Qualifications - To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• 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, NumPy, statsmodels
• 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

Preferred Qualifications:

• 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

Education

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

Total Perks Package

• 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 soft closing Christmas Eve-New Year's Day
• Paid leave options, including sick leave, medical leave for self and family, and parental leave

Position Summary

We are seeking a skilled Machine Learning Engineer with approximately three years of hands-on experience designing, deploying, and maintaining production-grade machine learning systems. In this role, you will collaborate closely with data scientists, software engineers, and product teams to translate research models into reliable, scalable, and high-impact applications. You will be deeply involved in the end-to-end ML lifecycle—from data ingestion and feature engineering to deployment, monitoring, and continuous improvement—playing a critical part in shaping our machine learning platform and capabilities.

Primary Responsibilities

• Develop, deploy, and optimize machine learning models for real-world business use cases and client-facing applications.
• Partner with data scientists to operationalize predictive models and ensure scalable, maintainable, and performant production deployments.
• Design and implement data pipelines and workflows that support training, inference, and model lifecycle management.
• Work with large, complex datasets to ensure data quality, reproducibility, and reliable version control across ML workflows.
• Implement model monitoring, logging, and alerting strategies to track performance, detect drift, and support retraining cycles.
• Leverage cloud platforms (AWS, Azure, GCP) to build scalable ML solutions using managed services and infrastructure-as-code practices.
• Write clean, modular, and well-documented code aligned with MLOps and software engineering best practices.
• Stay current on emerging ML tooling, frameworks, and industry best practices to continuously enhance our platform and capabilities.

Qualifications

• Master’s degree in Computer Science, Data Science, Engineering, or a related technical field.
• 6+ years of experience in machine learning engineering, applied ML, or related software engineering roles.
• Strong proficiency in Python and experience with modern ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Experience with distributed data processing and compute frameworks (e.g., Pandas, Spark, Dask).
• Hands-on experience with containerization and orchestration technologies such as Docker and Kubernetes.
• Familiarity with CI/CD pipelines, testing automation, and version control using Git.
• Experience working with cloud-based ML platforms or services (e.g., SageMaker, Vertex AI, Databricks, or Snowflake ML) is preferred.
• Strong understanding of model evaluation, feature engineering, and performance optimization in production contexts.
• Excellent analytical, communication, and collaboration skills, with the ability to work effectively in cross-functional teams.

This is an exempt position. The annualized base pay range for this role is expected to be between $140,000-$180,000.  Actual base pay could vary based on factors including but not limited to experience, subject matter expertise, geographic location where work will be performed, and the applicant's skill set.  The base pay is just one component of the total compensation package for employees.  Other rewards may include an annual cash bonus and a comprehensive benefits package, including but not limited to medical, dental, vision, life and 401(k). Please note that the job title is subject to change based on the selected candidate’s experience and education.