Web Marketing Program - Digital Experience Data Scientist

118-WW TMG MFG OPS; Dallas (TX); On-site; USD 120,000 - 150,000; Full time

Job summary

118-WW TMG MFG OPS in Dallas, TX seeks a talented Data Scientist to join our Digital Experience Analytics team. You will apply advanced analytics and ML to large customer datasets to power personalized digital experiences and measure their effectiveness.

Collaborate with marketing, sales, and IT to develop data products, deploy models in production, and drive business objectives. You will design experiments, run A/B tests, and stay at the forefront of data science innovations.

Qualifications

• Bachelor's degree in data science, CS, stats, or related field.
• Internship in data science or related role, preferably in sales/marketing/e-commerce.
• Experience deploying models in production and improving performance.
• Strong proficiency in Python or R for data analysis and ML.
• Experience with ML libraries such as Python, scikit-learn, PyTorch, Kubeflow, Streamlit.
• Expertise in statistical analysis, experimental design, and causal inference.
• Strong SQL skills and experience working with large datasets.
• Familiarity with cloud platforms (GCP, Vertex AI, AWS, Bedrock) and Unix/Linux.
• Innovator level knowledge of developments in data science and adjacent fields (e.g., Generative AI).
• Strong problem-solving and ability to translate analyses into insights.
• Excellent communication to present technical concepts.

Responsibilities

• Develop advanced ML models for personalization and journey optimization in a complex B2B model.
• Identify opportunities to use ML/AI and analytics to improve digital program design and effectiveness.
• Collaborate on recommender system components for hundreds of thousands of users.
• Create predictive models to segment, cluster and label customer behavior with analysts.
• Work with engineering teams to drive scalable, real-time implementations.
• Translate business requirements into data science solutions.
• Partner with UX to design and conduct A/B tests to optimize digital experiences.
• Ensure best practices and proper documentation/versioning of models.
• Stay current with data science advancements and apply new techniques.

Skills

Python

R

SQL

Machine Learning

Statistics

Experimentation

Communication

Data Visualization

Education

Bachelor's degree in Data Science, Computer Science, Statistics, Applied Mathematics or related field

Master's degree in Data Science, Computer Science, Statistics, Applied Mathematics or related field

Tools

scikit-learn

pyTorch

Kubeflow

Streamlit

Google Cloud Platform

Vertex AI

AWS

BedRock

Unix/Linux

Job description

Change the world. Love your job.
We are seeking a talented and innovative Data Scientist to join our Digital Experience Analytics team. Operating at the intersection of data science, marketing, and business strategy, you will apply advanced analytics and machine learning techniques to large customer datasets to power personalized digital experiences and measure their effectiveness.

The ideal candidate will have a background in data science, machine learning, and marketing analytics, with experience in developing and deploying machine learning models. You will collaborate closely with our marketing, sales, and enterprise IT teams to deliver data products that support key business objectives. If you enjoy solving complex problems, building foundational data products, and influencing overall business strategy, we’d love to hear from you.

Key Responsibilities

• Develop advanced machine learning models for personalization and customer journey optimization in a complex B2B business model.
• Identify opportunities to use machine learning, AI, and advanced analytics techniques to improve digital program design and effectiveness.
• Partner with other data scientists in the development of recommendation system components that predict relevant product and content messages for hundreds of thousands of users.
• Create predictive models to segment, cluster and label customer behavior, partnering with analysts to identify opportunities for targeted interventions.
• Work closely with engineering teams to drive scalable, real-time implementations.
• Collaborate with cross-functional teams to translate business requirements into data science solutions.
• Partner with Digital Experience & UX strategists to design and conduct A/B tests to optimize digital experiences and marketing campaigns.
• Ensure data science best practices are followed and models are properly documented and version-controlled.
• Stay current with the latest advancements in data science and apply new techniques to improve our analytics capabilities.

Minimum Requirements

• Bachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics or a related field.
• Internship experience in data science or a related role, preferably in a sales, marketing or e-commerce context.
• Experience deploying models in production and adjusting models to improve performance.
• Strong proficiency in Python or R for data analysis and machine learning.
• Experience with machine learning libraries such as Python, scikit-learn, pyTorch, Kubeflow, Streamlit, etc.
• Expertise in statistical analysis, experimental design, and causal inference.
• Strong proficiency in SQL and experience working with large datasets.
• Familiarity with both cloud-based data science platforms (e.g., Google Cloud Platform, Vertex AI, AWS, BedRock) and Unix/Linux systems.
• Innovator level knowledge of developments in data science and adjacent fields (e.g. Generative AI, Human-in-the-Loop workflows) and their application.
• Strong problem-solving skills and ability to translate complex analyses into actionable insights.
• Excellent communication skills, with the ability to present technical concepts to non-technical audiences.

Preferred Qualifications

• Master's degree in Data Science, Computer Science, Statistics, Applied Mathematics or a related field.
• Experience with marketing automation and CRM systems (e.g., Salesforce, Marketo, HubSpot).
• Experience with Graph Databases (e.g., Memgraph, Neo4j, SpannerGraph)
• Experience with Customer Data Platforms (e.g., Tealium, Segment, ActionIQ).
• Knowledge of client-side web analytics tools and techniques (e.g., GA4, Adobe Analytics, Fullstory).
• Experience with natural language processing (NLP) and text analytics.
• Understanding of digital marketing concepts and customer journey mapping.