Marketing Data Scientist

DigitalXNode; Chicago (IL); On-site; USD 110,000 - 160,000; Full time

Job summary

DigitalXNode is seeking a Marketing Data Scientist to design and deploy advanced analytics for marketing ROI measurement and attribution. You will build data-driven solutions using Python, time series analysis, and ML in AWS, collaborating with marketing, data science, and engineering teams to translate insights into business impact.

Responsibilities include developing production-grade analytics apps with Streamlit, delivering scalable data pipelines, and presenting insights to stakeholders to

Qualifications

• Strong Python coding skills for data science and analytics.
• Experience with large marketing performance data sets.
• Solid background in statistics and predictive modeling.

Responsibilities

• Develop and maintain ROI measurement models for marketing initiatives.
• Analyze marketing, advertising, and sales data to identify growth opportunities.
• Measure channel performance across digital and traditional marketing.
• Evaluate advertising effectiveness and campaign performance with analytics.
• Translate insights into actionable recommendations for optimization.

Skills

Python programming for data science

Time series analysis

Marketing analytics

Statistical modeling

Bayesian modeling

Linear regression

Time series forecasting

Data interpretation & communication

Education

Bachelor's degree in a quantitative field

Master's degree preferred

Certifications in Data Science / AWS (advantageous)

Tools

Pandas

NumPy

PyTest

Streamlit

Scikit-learn

Statsmodels

Jupyter Notebooks

AWS

S3

EC2

Job description

Marketing Data Scientist | Mexico, Chicago

We are seeking a highly analytical and data-driven Marketing Data Scientist to support the development, optimization, and enhancement of advanced marketing analytics and ROI measurement platforms. This role focuses on leveraging statistical modeling, machine learning techniques, and data science methodologies to evaluate marketing performance, optimize advertising investments, and generate actionable business insights.

The ideal candidate will possess strong expertise in Python, time series analysis, marketing analytics, and statistical modeling while also demonstrating solid software engineering and cloud platform experience. You will work closely with business stakeholders, marketing teams, data scientists, and engineers to build scalable analytical solutions that improve decision-making and maximize marketing effectiveness.

This position offers the opportunity to contribute directly to production-grade machine learning applications while collaborating with experienced domain experts in marketing science, analytics, and data engineering.

Key Responsibilities

Marketing Analytics & Performance Measurement

• Develop, maintain, and enhance marketing effectiveness and ROI measurement models.
• Analyze marketing, advertising, and sales performance data to identify growth opportunities and optimization strategies.
• Measure channel performance across digital and traditional marketing initiatives.
• Evaluate advertising effectiveness and campaign performance using advanced analytical techniques.
• Generate actionable recommendations to improve marketing investments and business outcomes.

Statistical Modeling & Data Science

• Build and deploy statistical models using Bayesian and linear modeling techniques.
• Develop predictive and explanatory models to understand marketing contribution and revenue impact.
• Perform time series analysis to evaluate trends, seasonality, and forecasting opportunities.
• Identify key business drivers influencing customer acquisition, engagement, and conversion performance.
• Support continuous model validation, enhancement, and optimization activities.

Business Collaboration & Insights

• Partner with business stakeholders to understand analytical requirements and strategic objectives.
• Present model outputs, insights, and recommendations to technical and non-technical audiences.
• Translate complex analytical findings into meaningful business insights.
• Support data-driven decision-making across marketing and leadership teams.
• Contribute to strategic discussions around marketing optimization and growth initiatives.

Application Development & Reporting

• Develop and enhance Streamlit-based analytical applications and dashboards.
• Build scalable Python-based workflows for data processing, reporting, and model execution.
• Create automated reporting solutions and export analytical outputs using Excel and related formats.
• Improve user experience and functionality of reporting platforms.
• Ensure analytical tools remain reliable, scalable, and maintainable.

Data Engineering & Cloud Operations

• Design and maintain efficient data workflows and analytical pipelines.
• Work within AWS environments to support data processing and application deployment.
• Manage and utilize AWS services including S3 and EC2.
• Collaborate with engineering teams to improve code quality, scalability, and maintainability.
• Support deployment and monitoring of production analytics solutions.

Monitoring & Optimization

• Monitor analytical applications and workflows using DataDog or similar monitoring platforms.
• Troubleshoot issues related to data processing, model execution, and application performance.
• Optimize workflows to improve efficiency, reliability, and scalability.
• Implement software engineering best practices for testing and quality assurance.

Required Skills

Data Science & Analytics

• Strong experience in Python programming for data science and analytics.
• Experience working with large datasets and marketing performance data.
• Strong understanding of statistical analysis and predictive modeling.
• Hands-on experience with:
  • Bayesian Modeling
  • Linear Regression Models
  • Time Series Analysis
  • Forecasting Techniques
• Ability to interpret and communicate analytical findings effectively.

Python & Data Science Libraries

• Pandas
• NumPy
• PyTest
• Streamlit
• Scikit-learn (preferred)
• Statsmodels (preferred)
• Jupyter Notebooks

Marketing Analytics

• Understanding of marketing performance measurement frameworks.
• Experience evaluating campaign effectiveness and marketing ROI.
• Knowledge of customer acquisition, attribution, and performance metrics.
• Ability to analyze multi-channel marketing data.
• Experience translating marketing data into business insights.

Cloud & Engineering Skills

• Experience working with AWS cloud services, including:
  • Amazon S3
  • Amazon EC2
• Knowledge of software engineering best practices.
• Familiarity with testing frameworks and code quality standards.
• Understanding of scalable application development and deployment workflows.
• Experience working in collaborative development environments.

Preferred Skills

• Experience with Marketing Mix Modeling (MMM).
• Experience in marketing analytics, advertising technology, or digital marketing environments.
• Familiarity with attribution modeling and customer journey analysis.
• Knowledge of ROI optimization frameworks.
• Exposure to machine learning deployment workflows.
• Experience with DataDog or similar monitoring solutions.
• Familiarity with experimentation and A/B testing methodologies.
• Spanish language proficiency is considered an advantage.

Education

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering, Marketing Analytics, or a related quantitative field.
• Master's degree in Data Science, Analytics, Statistics, Applied Mathematics, Machine Learning, or a related discipline is preferred.
• Relevant certifications in Data Science, AWS, Analytics, or Machine Learning are advantageous.