Pay
$118K–$193K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 3,721 postings in the last year. Stated ranges, not salaries paid.
Web Marketing Program - Digital Experience Data Scientist
Dallas, TX, United States
Live, first seen by us 54 days ago- Pay
- Pay not listedSimilar roles state $118K–$193K
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingDevelop machine learning models for personalization and customer journey optimization
Build recommendation system components that predict relevant product and content messages
Segment, cluster and label customer behavior with predictive models
Design and conduct A/B tests to optimize digital experiences and campaigns
Work with engineering teams on scalable, real-time model implementations
From the employer’s posting
Develop advanced machine learning models for personalization and customer journey optimization in a complex B2B business model.
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
Partner with Digital Experience & UX strategists to design and conduct A/B tests to optimize digital experiences and marketing campaigns.
Work closely with engineering teams to drive scalable, real-time implementations.
What you’ll bring
All qualificationsCore experience
- Bachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics or a related field.
Preferred experience
- Master's degree in Data Science, Computer Science, Statistics, Applied Mathematics or a related field.
- 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.
Qualification wording
Bachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics or a related field.
Master's degree in Data Science, Computer Science, Statistics, Applied Mathematics or a related field.
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.
Education & alternatives
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.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 12, 202654 days ago
- Recorded sightings
- 223
- Last seen by us
- Nov 5, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 54
Similar jobs usually come down between day 7 and day 56.
Well past Texas Instruments’s usual: its jobs come down by about day 12.
From 10,194 similar postings that came down, and 13 of Texas Instruments’s. Coming down is not always a hire.
Texas Instruments is hiring
7 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring has slowed
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- R
- SQL
- AWS
- Neo4j
- PyTorch
- scikit-learn
- Streamlit
- GCP
Where the posting names them
- 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.
- 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.
- 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.
- 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.
- 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).
Your next step
Complete your application on edbz.fa.us2.oraclecloud.com. The employer’s form will show what is required.
Applying through Oracle Recruiting
- Applying starts by asking for your email address.
- Each employer sets which files it accepts, so read the note beside the upload field.
Already applied? Track this application
About Texas Instruments
- People
- About 33,000 in 2025, down 3% from the year before.Annual report (SEC Form 10-K)
- Company
- Listed as TXN.
- H-1B visas
- 54 approved for new hires in fiscal 2025.US Citizenship and Immigration Services
Demand for Data Scientist roles
New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
US government figures for data scientists
- Median yearly pay, May 2025
- $120,230
- Expected change, 2025 to 2035
- 34.6% more jobsagainst 3.5% for all jobs
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
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.
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.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Dallas, TX, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.