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Manager Causal Inference Jobs in Texas (NOW HIRING)

Knowledge of Terraform and Ansible for automating infrastructure management * Knowledge of YAML for ... causal inference. * Handson experience in geospatial data analyticsusing Esri products, with a ...

The company leverages its global leadership in carbon management to advance lower-carbon ... inference, Markov chain Monte Carlo (MCMC), and causal inference. * Hands-on experience in ...

Senior Manager, Data Science We are Lennar Lennar is one of the nation's leading homebuilders ... causal inference, reinforcement learning, or simulation modeling; exposure to LLM-based ML use ...

... management platform. This role requires a technical expert who can develop, deploy, and maintain ML ... Strong foundation in statistics, A/B testing, causal inference, and experimental design • ...

Collaborate closely with product managers, software engineers, and domain experts to deliver ... Strong foundation in statistics, experimental design, and causal inference * Experience working ...

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Manager Causal Inference information

How does a Manager of Causal Inference typically collaborate with cross-functional teams to drive impactful business insights?

Managers of Causal Inference frequently work alongside data scientists, product managers, engineers, and business leaders to design and execute experiments that reveal the true impact of business decisions. They translate complex statistical findings into actionable recommendations, ensuring stakeholders understand both the methodology and implications. Regularly, they lead discussions on experiment design, data collection strategies, and result interpretation, fostering a culture of evidence-based decision-making across the organization.

What does a Manager Causal Inference do?

A Manager Causal Inference leads teams that analyze data to determine cause-and-effect relationships, often in business, healthcare, or technology settings. They design experiments or use statistical methods to understand how different factors influence outcomes, helping organizations make data-driven decisions. This role typically involves managing projects, overseeing analysts or data scientists, and communicating findings to stakeholders. Strong expertise in statistics, data analysis, and leadership is essential for success in this position.

What are the key skills and qualifications needed to thrive as a Manager of Causal Inference, and why are they important?

To thrive as a Manager of Causal Inference, you need a deep understanding of statistics, econometrics, and experimental design, typically supported by an advanced degree in a quantitative field. Proficiency with data analysis tools such as R, Python, SQL, and specialized causal inference libraries, along with experience using data visualization and project management platforms, is crucial. Strong leadership, communication, and critical thinking skills help you effectively guide teams and translate complex findings to stakeholders. These skills ensure rigorous, actionable insights that drive strategic decision-making and organizational impact.
What are the most commonly searched types of Causal Inference jobs in Texas? The most popular types of Causal Inference jobs in Texas are:
What are popular job titles related to Manager Causal Inference jobs in Texas? For Manager Causal Inference jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Manager Causal Inference jobs in Texas look for? The top searched job categories for Manager Causal Inference jobs in Texas are:
What cities in Texas are hiring for Manager Causal Inference jobs? Cities in Texas with the most Manager Causal Inference job openings:
Sr AI Engineer - San Jose or Frisco

Sr AI Engineer - San Jose or Frisco

Syndesus, Inc.

Dallas, TX

$180K - $230K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 7 days ago


Job description

Senior AI Engineer - MarTech / Marketing Intelligence Hybrid | San Jose, CA or Frisco, TX (must be locally based | (no relocation)
The Role
Senior AI Engineering role architecting the intelligence layer behind a global consumer software company's marketing ecosystem. You'll move the org from manual campaign management to autonomous campaign orchestration - designing agentic workflows, generative creative pipelines, and real-time personalization systems that operate with minimal human intervention.
This is a hands-on, build-it role at the intersection of MarTech and applied AI.
Responsibilities
  • Architect and deploy AI agents for cross-channel campaign orchestration, real-time lead qualification, and end-to-end workflow automation
  • Build scalable generative asset pipelines for automated ad creative (text, image, video) using LLMs and multimodal models, with brand-safe guardrails
  • Implement RAG systems for context-aware, personalized content across web, email, and SMS
  • Develop and productionalize ML models for LTV prediction, churn propensity, and Next Best Action engines
  • Own the full MLOps lifecycle - feature engineering, deployment, monitoring for data drift
  • Ensure compliance with global privacy standards (GDPR, CCPA) and implement privacy-first AI techniques (differential privacy, synthetic data)
  • Establish Responsible AI governance frameworks across the marketing function
Requirements
  • Strong SQL and cloud data warehouse experience; Databricks for feature engineering a strong plus
  • MarTech integration experience - CDPs (HighTouch), ESPs (Braze, Iterable), Ad Platforms (Meta Conversions API, Google Enhanced Conversions), Analytics (Adobe CJA)
  • Deployment fluency with Docker, Kubernetes, and cloud AI services (SageMaker, Vertex AI, or Azure AI Studio)
  • Previous experience in a high-growth B2C marketing environment
  • Ability to translate vague marketing goals into concrete technical requirements
Nice to Have
  • Experience developing applications or integrations across Windows, macOS, iOS, or Android ecosystems
  • Customer-facing web experience (JavaScript, Adobe Experience Manager)
  • Expert Python; deep experience with PyTorch or TensorFlow
  • Hands-on with LLM orchestration frameworks (LangChain, LlamaIndex, LangGraph)
  • Production experience with RAG systems and vector databases (Pinecone, Milvus, Weaviate)
  • Fine-tuning experience (LoRA, QLoRA) with frontier LLMs
  • Strong grounding in Bayesian A/B testing and causal inference
The Stack
  • Data: Databricks, HighTouch
  • AI/ML: Claude, PyTorch, Hugging Face, OpenAI API, LangGraph
  • Orchestration: Airflow, Prefect, GitHub Actions
  • Marketing Execution: Braze
  • Monitoring: Weights & Biases, Arize, Grafana
  • Analytics: Adobe CJA

Compensation
$180,000 - $230,000 USD base + bonus program
The Company
Well-established, globally recognized consumer software company with strong perks: bonus program, 401k, medical/dental/vision, paid parental leave, 14 paid holidays, and unlimited PTO for exempt employees.
Compensation
The base pay range for this role is $180,000 - $230,000 per year.