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Manager Causal Inference Jobs in Texas (NOW HIRING)

Principal AI/ML Software Engineer

Houston, TX · On-site

$128K - $172K/yr

... 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 • ...

Marketing Analytics Lead

Austin, TX · On-site

$150 - $200/hr

You're fluent in the craft and exceptional at stakeholder management, influence, and storytelling ... with causal inference. Comfortable with the tactical underpinnings -- data integrations ...

Senior Data Scientist

Austin, TX · On-site

$100 - $125/hr

We are a fully transparent platform built with top technology, countless programmatic management ... Solid understanding of statistical concepts, hypothesis testing, causal inference, and regression ...

We are a fully transparent platform built with top technology, countless programmatic management ... Solid understanding of statistical concepts, hypothesis testing, causal inference, and regression ...

We are a fully transparent platform built with top technology, countless programmatic management ... Solid understanding of statistical concepts, hypothesis testing, causal inference, and regression ...

You're fluent in the craft and exceptional at stakeholder management, influence, and storytelling ... causal inference. Comfortable with the tactical underpinnings - data integrations, attribution ...

... 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 ...

$35/hr

Demonstrated leadership, problem-solving, and organizational skills with the ability to manage ... Familiarity with causal inference methods (propensity score matching, instrumental variables) and ...

$35/hr

Demonstrated leadership, problem-solving, and organizational skills with the ability to manage ... Familiarity with causal inference methods (propensity score matching, instrumental variables) and ...

Showing results 41-60

Manager Causal Inference information

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 causal inference?

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.

How does a manager 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 are the most commonly searched types of Causal Inference jobs in Texas?

The most popular types of Causal Inference jobs in Texas 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:

Principal AI/ML Software Engineer

Hexagon AB

Houston, TX • On-site

$128K - $172K/yr

Full-time

Re-posted 15 hours ago


Job description

Principal AI/ML Software Engineer
Job Location (Short): Houston, Texas-USA | Madison, Alabama-USA
Workplace Type: Remote
Req Id: 2909
Responsibilities
Position Overview
We are seeking a motivated AI/ML Engineer to build reliable, scalable systems and Generative AI and Agentic AI features, and build and deploy data-driven solutions for our document-based compliance management platform. This role requires a technical expert who can develop, deploy, and maintain ML systems in production environments.
Key Responsibilities
• Build and deploy Generative AI features using foundation models (AWS Bedrock, OpenAI, Anthropic Claude) and inference pipelines with optimization of latency and cost
• Design agentic AI systems that autonomously handle compliance workflows, document review, regulatory mapping, and multi-step reasoning tasks
• Integrate comprehensive LLM evaluation frameworks with development and production systems
• Build and operate end-to-end MLOps pipelines, deployment systems, monitoring, and rollbacks workflows
• Implement explainability frameworks (SHAP/LIME) and monitoring dashboards ensuring transparency and regulatory adherence
• Collaborate with cross-functional teams to translate business needs into ML solutions and communicate insights to stakeholders
#LI-PB1 LI-Remote
Education / Qualifications
Technical Skills
• Python (5+ years): Production-level experience with Pandas, NumPy, scikit-learn, XGBoost, TensorFlow/PyTorch, Hugging Face Transformers, FastAPI/Flask, MLflow, and pytest
• SQL: Advanced proficiency with complex queries, window functions, and optimization
• Machine Learning & NLP: Strong foundation in supervised/unsupervised learning, deep learning, document understanding, text classification, and semantic analysis
• Generative AI & LLMs: Hands-on experience with foundation models (GPT, Claude, Llama), prompt engineering, RAG architectures, and vector databases (Pinecone, Weaviate, Chroma)
• MLOps & ModelOps: End-to-end experience with ML pipelines, model versioning, feature stores, drift detection, CI/CD for ML, and Docker containerization
• LLM Evaluation: Experience with evaluation frameworks (RAGAS, DeepEval), custom metrics, benchmark datasets, and human-in-the-loop validation
• Cloud & AWS: Experience with AWS services including SageMaker, Bedrock, S3, Lambda, EC2, and CloudWatch
• Statistics & Experimentation: Strong foundation in statistics, A/B testing, causal inference, and experimental design
• Visualization: Proficiency with Tableau, Power BI, or Python visualization libraries
Experience & Education
• 5+ years in data science, ML engineering, or related roles
• 3+ years building NLP/generative AI applications and implementing MLOps in production
• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or related field
• Track record of deploying ML systems processing large-scale datasets with proper monitoring and governance
Preferred Qualifications
• Experience with agentic AI frameworks (LangGraph, LangChain, AutoGen, CrewAI) ?
• Knowledge of Life Sciences/regulated industries (FDA, EMA, ISO, GxP) and compliance management systems
• Familiarity with big data tools (Spark, Databricks, Snowflake), orchestration (Airflow, Kubeflow), and monitoring tools (Datadog, Prometheus)
• Experience with LLM fine-tuning, document processing libraries, multi-modal AI, or distributed training
• Understanding of ML governance, bias detection, model risk management, and data privacy regulations (GDPR, CCPA, HIPAA)
• Experience working in agile environments with Jira
• AWS ML certifications or similar credentials
Key Competencies
• Strong communication skills explaining complex models to technical and nontechnical audiences
• Ability to work independently and collaboratively in fast-paced environments
• Proven ability to convert POCs into production-grade solutions
• Understanding of ethical AI and building trustworthy, explainable systems for regulated environments
What You'll Build
• LLM evaluation frameworks ensuring 95%+ accuracy for compliance-critical features
• Prompts for LLMs to achieve specific, high-quality outcomes
• Agentic AI systems autonomously handling document review and compliance workflows
• GenAI document understanding features processing millions of regulatory documents
• Predictive models identifying compliance risks before they occur
• Real-time semantic search and explainable ML systems meeting regulatory requirements
• Production MLOps pipelines supporting dozens of models with automated monitoring and retraining
Growth Opportunities
• Drive adoption of emerging AI technologies and establish best practices
• Mentor ML engineers
• Shape AI/ML roadmap and establish center of excellence for compliance AI
• Collaborate with product leadership on long-term vision for AI-powered compliance
About Octave
Octave provides mission-critical software that empowers organizations to make informed decisions across every stage of the asset lifecycle - Design, Build, Operate and Protect - where performance, safety, and reliability are non-negotiable and failure is not an option.
Turning complex operational data into actionable intelligence, Octave connects expertise, real-world conditions and enterprise-scale insight to improve performance, resilience and incident response where it matters most.
Octave has more than 7,000 employees in 45 countries. Learn more at octave.com and follow us on LinkedIn.
Why work for Octave?
All in. Always forward. That's the way we do things around here. We put trust in our people because we believe it's the best way to unleash potential, bring ideas to life, and keep moving ahead. And it's why we're committed to creating an environment that's truly supportive, providing you with the resources you need to support your ambitions, no matter who you are or where you are in the world.
Everyone is welcome
At Octave, we believe that diverse and inclusive teams are critical to the success of our people and our business. Here, everyone is welcome. As an inclusive workplace, we don't discriminate. In fact, we embrace differences and are fully committed to creating equal opportunities, an inclusive environment, and fairness for all.
Respect is the cornerstone of how we operate, so speak up and be yourself. You're valued here.
Recruitment Fraud Alert
Octave posts all official job opportunities on either https://careers.octave.com/ or https://www.octave.com/about/careers and communicates only from email addresses ending in @octave.com. We never request payment or personal banking information during recruitment. No offers will ever be extended without a proper interview via Teams or in person, never done over email alone. If you suspect fraud, it probably is, and contact us at careers@octave.com