Web Marketing Program - Digital Experience Data Scientist
At a glance
Mid-level Data Science role at Edbz. Dallas · full-time · no salary stated · we estimate $116,263–$174,915 across the United States.
Edbz has not published a salary for this role. The figure below is our estimate, not theirs.
dataroles summary, based on the employer's posting.
What you'll do
- Build machine-learning models that personalize digital experiences and improve customer journeys in a B2B setting
- Create recommendation components that select relevant product and content messages for large user groups
- Use customer behavior models to form segments and identify audiences for targeted interventions
- Work with engineering to put models into scalable, real-time use and with UX teams to test digital experiences
- Document and version-control models while turning business needs into data science solutions
What you bring
- A bachelor’s degree in data science, computer science, statistics, applied mathematics or a related field
- A cumulative GPA of at least 3.0 on a 4.0 scale
- Preferred: practical model deployment experience, strong Python or R skills, and work with machine-learning libraries
- Preferred: statistical analysis and experimental design experience, plus confidence working with SQL and large datasets
Who this fits
This mid-level role suits someone who combines data science with marketing analytics and can work across marketing, sales, IT, engineering and UX teams. A bachelor’s degree and the stated GPA threshold are required; the advanced degree and technical experience are preferred.
From the employer
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.
Cumulative GPA of 3.0/4.0
Preferred Qualifications:
- Master'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.
- 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.
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