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Manager Causal Inference Jobs in Texas (NOW HIRING)

Senior AI Engineer, MarTech

Frisco, TX · On-site

$115K - $152K/yr

... testing and causal inference to measure the true uplift of AI interventions. • Ability to ... and managing vector databases (Pinecone, Milvus, or Weaviate). • Experience developing ...

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 ...

Principal Data Scientist

Austin, TX · On-site

$215K - $235K/yr

... power how clients manage their money, supporting Schwab's commitment to expanding access to ... Strong background in statistics, forecasting, or causal inference. * Hands-on experience ...

Principal AI/ML Software Engineer

Houston, TX · On-site

$124K - $167K/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 • ...

... power how clients manage their money, supporting Schwab's commitment to expanding access to ... Strong background in statistics, forecasting, or causal inference. * Hands‑on experience ...

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

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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.
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What cities in Texas are hiring for Manager Causal Inference jobs? Cities in Texas with the most Manager Causal Inference job openings:
Senior Product Analyst

Senior Product Analyst

SRI Tech Solutions Inc

Austin, TX • On-site

Contractor

Re-posted 11 days ago


Job description

Role: Senior Product Analyst

Location: Austin, TX (onsite)

Role Summary:

The Senior Product Analyst is responsible for measuring and analyzing how effectively customer service tools and AI-driven automation features support both agents and customers. This role combines analytical rigor with a product mindset. The scope includes evaluating the productivity impact of existing systems, quantifying the value of new features, and identifying opportunities to enhance speed, quality, and automation through data-driven insights.

You’ll work cross-functionally with Product, BPR and technical teams (AI/LLM & dev teams) to translate raw data into clear business recommendations that improve customer experiences and reduce handling effort across human and automated interactions. Partner with Product Managers to scope solutions, refine backlogs, and align dependencies across Contact Center and digital platforms.

Key Responsibilities:

  • Measure the efficiency and effectiveness of customer and internal facing enterprise tools (Chat, telephony, workflow and AI/LLM systems).
  • Develop and maintain dashboards and performance models tracking key metrics targeted for improvement such as handle time, automation rate, accuracy, and customer satisfaction.
  • Evaluate the ROI and adoption of new features, quantifying value through productivity improvements, cost savings, or customer impact.
  • Influence the product roadmap through data driven insights
  • Partner with engineering and AI teams to analyze LLM bot interactions, comparing outcomes against human agent performance (speed, resolution quality, escalation rates).
  • Identify bottlenecks and propose data-backed recommendations to improve tool usability, automation coverage, and integration efficiency.
  • Translate insights into clear narratives and presentations for leadership, highlighting business impact and next-step recommendations

Required Skills & Qualifications:

  • Analytical Expertise: Excellent SQL skills (Snowflake preferred) and experience in data visualization tools (Tableau preferred)
  • Experimentation & Measurement: Knowledge of A/B testing, causal inference, and performance benchmarking.
  • Product & Process Understanding: Familiarity with contact-center workflows, CRM/ticketing tools (Salesforce, Genesys, etc.), and LLM-driven automation systems.
  • Statistical & ML Awareness: Understanding of accuracy metrics, confusion matrices, and model performance trade-offs when comparing human vs. AI output.
  • Business Acumen: Ability to translate complex data into clear business stories that drive action.
  • Collaboration & Communication: Strong cross-functional skills; able to partner with engineers, data scientists, and operations teams effectively.
  • Preferred Tools: SQL, Python (for data analysis), Tableau (visualization)

Preferred Background:

  • 6-10 years of experience in analytics, product operations, or data-driven process improvement.
  • Experience working in e-commerce, customer service, automation, or LLM-based platforms.
  • Exposure to contact center analytics, AI evaluation, or operational excellence functions.
SRI Tech Solutions is an equal opportunity employer and does not discriminate on the basis of race, color, gender, religion, age, sexual orientation, national origin or citizenship status or ethnic origin, disability, marital status, veteran status, or any other occupationally irrelevant criteria.