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Manager Causal Inference Jobs in Utah (NOW HIRING)

... business managers. Incumbents whose primary role is technical and focused on data storage ... and causal inference. * Proficiency in SQL for data querying and manipulation, with experience ...

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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 Utah?

The most popular types of Causal Inference jobs in Utah are:

What are popular job titles related to Manager Causal Inference jobs in Utah?

For Manager Causal Inference jobs in Utah, the most frequently searched job titles are:

What job categories do people searching Manager Causal Inference jobs in Utah look for?

The top searched job categories for Manager Causal Inference jobs in Utah are:

What cities in Utah are hiring for Manager Causal Inference jobs?

Cities in Utah with the most Manager Causal Inference job openings:

Infographic showing various Manager Causal Inference job openings in Utah as of August 2026, with employment types broken down into 86% Full Time, 13% Part Time, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution.

Senior Data Scientist

Patientco

Lehi, UT • On-site

Full-time

Medical, Retirement, PTO

Posted 25 days ago


Job description

ABOUT THIS POSITION

Designs, develops and programs methods, processes, and systems to consolidate and analyze unstructured, diverse "big data" sources to generate actionable insights and solutions for client services and product enhancement. Interacts with product and service teams to identify questions and issues for data analysis and experiments. Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources. Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers. Incumbents whose primary role is technical and focused on data storage, warehousing and systems architecture should be matched to Database Engineering or Storage Engineering. Incumbents whose focus is the quantitative analysis of complex business problems and issues using data from internal and external sources to provide insight to decision-makers should be matched to Business Intelligence. Incumbents whose primary role is technical and focused on designing and building system-generated reports, reporting tools and dashboards for data generation should be matched to Data Informatics. Incumbents whose focus is primarily on experimental design and advanced or complex statistical analysis and modeling of datasets should be matched to Statistician/Mathematician. This is a product engineering role in which employees work with multiple types of business data. Incumbents whose focus is primarily on analysis and modeling of financial, marketing or pricing data should be matched to Finance, Market Research or Pricing as appropriate. May be internal operations-focused or external client-focused, working in conjunction with Professional Services and outsourcing functions.

WHAT YOU'LL DO

* Lead the design, development, and implementation of sophisticated machine learning models and predictive analytics solutions to solve critical business problems.
* Mentor and guide junior data scientists, fostering a culture of excellence and continuous learning within the team.
* Collaborate with cross-functional teams (engineering, product, business stakeholders) to define data science project requirements, scope, and deliverables.
* Conduct in-depth data exploration, analysis, and visualization to identify trends, patterns, and anomalies, presenting findings clearly and concisely to diverse audiences.
* Develop and maintain robust data pipelines and infrastructure in collaboration with data engineers to ensure data quality, accessibility, and integrity.
* Stay abreast of the latest advancements in data science, machine learning, and artificial intelligence, evaluating and recommending new technologies and methodologies.
* Contribute to the strategic direction of Waystar's data science initiatives, identifying opportunities for innovation and impact.
* Champion data-driven decision-making throughout the company, educating and influencing stakeholders on the power of data science.
* Evaluate and select appropriate statistical methods and machine learning algorithms for various business challenges, ensuring rigor and validity.

WHAT YOU'LL NEED

* Master's or Ph.D. in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
* 8+ years of progressive experience in data science, with a proven track record of delivering impactful data-driven solutions in a fast-paced environment.
* Expert-level proficiency in Python and/or R for data manipulation, statistical analysis, and machine learning model development.
* Extensive experience with various machine learning techniques (e.g., supervised, unsupervised, reinforcement learning, deep learning) and their practical applications.
* Strong understanding of statistical modeling, experimental design, hypothesis testing, and causal inference.
* Proficiency in SQL for data querying and manipulation, with experience working with large-scale datasets.
* Experience with cloud platforms (e.g., AWS, Azure, GCP) and big data technologies (e.g., Spark, Hadoop) is highly desirable.
* Excellent communication, presentation, and interpersonal skills, with the ability to explain complex technical concepts to non-technical stakeholders.
* Demonstrated ability to lead projects, mentor team members, and drive successful outcomes.
* Prior experience in the healthcare technology or financial services industry is a plus.

ABOUT WAYSTAR

Through a smart platform and better experience, Waystar helps providers simplify healthcare payments and yield powerful results throughout the complete revenue cycle.

Waystar's healthcare payments platform combines innovative, cloud-based technology, robust data, and unparalleled client support to streamline workflows and improve financials so providers can focus on what matters most: their patients and communities. Waystar is trusted by 1M+ providers, 1K+ hospitals and health systems, and is connected to over 5K commercial and Medicaid/Medicare payers. We are deeply committed to living out our organizational values: honesty; kindness; passion; curiosity; fanatical focus; best work, always; making it happen; and joyful,optimistic & fun.

Waystar products have won multiple Best in KLAS or Category Leader awards since 2010 and earned multiple #1 rankings from Black Book surveys since 2012. The Waystar platform supports more than 500,000 providers, 1,000 health systems and hospitals, and 5,000 payers and health plans. For more information, visit waystar.comor follow @Waystaron Twitter.

WAYSTAR PERKS

  • Competitive total rewards (base salary + bonus, if applicable)
  • Customizable benefits package (3 medical plans with Health Saving Account company match)
  • We offer generous paid time off for our non-exempt team members, starting with 3 weeks +13 paid holidays, including 2 personal floating holidays. We also offer flexible time off for our exempt team members + 13 paid holidays
  • Paid parental leave (including maternity + paternity leave)
  • Education assistance opportunities and free LinkedIn Learning access
  • Free mental health and family planning programs, including adoption assistance and fertility support
  • 401(K) program with company match
  • Pet insurance
  • Employee resource groups

Waystar is proud to be an equal opportunity workplace. We celebrate, value, and support diversity and inclusion. Qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, marital status, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.