{"id":3122637,"url":"https://alion.io/job/texas-instruments-web-marketing-program-digital-experience-data-scientist","title":"Web Marketing Program - Digital Experience Data Scientist","company":{"id":36400,"name":"Texas Instruments","domain":"ti.com","url":"https://alion.io/company/texas-instruments","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"B","score":76,"open_postings":208,"ghost_share":0,"stale_share":0.942,"repost_share":0,"time_to_fill_p50_days":28,"computed_at":"2026-11-08T05:47:12Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Dallas, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":104000,"max_usd":225000,"period":"year","method":"role_country_seniority_unknown","sample_n":3718},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Machine Learning","optional":false},{"name":"Recommender Systems","optional":false},{"name":"AWS","optional":true},{"name":"GCP","optional":true},{"name":"Human-in-the-Loop","optional":true},{"name":"Kubeflow","optional":true},{"name":"Linux","optional":true},{"name":"Memgraph","optional":true},{"name":"Neo4j","optional":true},{"name":"NLP","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true},{"name":"Scikit-learn","optional":true},{"name":"SQL","optional":true},{"name":"Streamlit","optional":true},{"name":"Unix","optional":true},{"name":"Vertex AI","optional":true}],"status":"live","first_seen_at":"2026-09-11T20:56:00Z","employer_posted_date":"2026-09-11","last_verified_at":"2026-11-07T21:53:22Z","board_verified":true,"closed_at":null,"days_open":57,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":57},"description":"Change the world. Love your job.\nWe 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.\nThe 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.\nKey Responsibilities:\nDevelop advanced machine learning models for personalization and customer journey optimization in a complex B2B business model.\nIdentify opportunities to use machine learning, AI, and advanced analytics techniques to improve digital program design and effectiveness. \nPartner with other data scientists in the development of recommendation system components that predict relevant product and content messages for hundreds of thousands of users.\nCreate predictive models to segment, cluster and label customer behavior, partnering with analysts to identify opportunities for targeted interventions.\nWork closely with engineering teams to drive scalable, real-time implementations.\nCollaborate with cross-functional teams to translate business requirements into data science solutions.\nPartner with Digital Experience & UX strategists to design and conduct A/B tests to optimize digital experiences and marketing campaigns.\nEnsure data science best practices are followed and models are properly documented and version-controlled.\nStay current with the latest advancements in data science and apply new techniques to improve our analytics capabilities.\n Minimum Requirements:\nBachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics or a related field.\nCumulative GPA of 3.0/4.0\n\nPreferred Qualifications:\nMaster's degree in Data Science, Computer Science, Statistics, Applied Mathematics or a related field.\nInternship experience in data science or a related role, preferably in a sales, marketing or e-commerce context.\nExperience deploying models in production and adjusting models to improve performance.\nStrong proficiency in Python or R for data analysis and machine learning.\nExperience with machine learning libraries such as Python, scikit-learn, pyTorch, Kubeflow, Streamlit, etc.\nExpertise in statistical analysis, experimental design, and causal inference.\nStrong proficiency in SQL and experience working with large datasets.\nFamiliarity with both cloud-based data science platforms (e.g., Google Cloud Platform, Vertex AI, AWS, BedRock) and Unix/Linux systems.\nInnovator level knowledge of developments in data science and adjacent fields (e.g. Generative AI, Human-in-the-Loop workflows) and their application.\nStrong problem-solving skills and ability to translate complex analyses into actionable insights.\nExcellent communication skills, with the ability to present technical concepts to non-technical audiences.\nExperience with marketing automation and CRM systems (e.g., Salesforce, Marketo, HubSpot).\nExperience with Graph Databases (e.g., Memgraph, Neo4j, SpannerGraph)\nExperience with Customer Data Platforms (e.g., Tealium, Segment, ActionIQ).\nKnowledge of client-side web analytics tools and techniques (e.g., GA4, Adobe Analytics, 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