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Bayesian Modeling Jobs in Texas (NOW HIRING)

Leidos

Spaceflight Data Scientist (NASA HHPC)

Houston, TX · On-site

$107K - $195K/yr

Develop, implement, and compare Bayesian decision-theoretic and normative decision-analytic models to guide contamination-risk and policy decisions for Mars sample return and backwards planetary ...

Apple

Data Center - MLB Reliability Engineer

Austin, TX

$101K - $127K/yr

Develop advanced reliability models such as Reliability Block Diagrams (RBDs), Markov Chains, and Bayesian analysis to quantify board-level risk and its contribution to overall system availability.

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Bayesian Modeling information

What is the difference between Bayesian Modeling vs Data Scientist?

AspectBayesian ModelingData Scientist
Required CredentialsStatistics, Mathematics, Data AnalysisStatistics, Computer Science, Data Analysis
Work EnvironmentResearch-focused, statistical modelingCross-functional, data analysis, visualization
Industry UsageResearch, academia, specialized analyticsBusiness, tech, finance, healthcare
Common Search/ComparisonYesYes

Bayesian Modeling and Data Scientists often overlap in skills like statistics and data analysis. Bayesian Modeling specializes in probabilistic models and statistical inference, while Data Scientists have broader roles including data cleaning, visualization, and machine learning. Both roles are essential in data-driven industries, but Bayesian Modeling is more focused on advanced statistical techniques.

What are the key skills and qualifications needed to thrive as a Bayesian modeler, and why are they important?

To thrive as a Bayesian Modeler, you need a solid background in statistics, probability theory, and mathematical modeling, often supported by an advanced degree in statistics, mathematics, or a related field. Proficiency with programming languages such as R, Python, or Stan, and experience with statistical software and Bayesian inference tools are essential. Strong analytical thinking, attention to detail, and effective communication skills help in interpreting results and collaborating with multidisciplinary teams. These skills ensure accurate model development, reliable data-driven insights, and clear communication of complex findings to stakeholders.

How does a Bayesian modeling specialist typically collaborate with cross-functional teams in a workplace setting?

Bayesian Modeling specialists often work closely with data scientists, software engineers, and domain experts to integrate probabilistic models into larger analytical or production systems. They are involved in translating complex statistical concepts into actionable insights and recommendations tailored to business needs. Effective communication is key, as they must present findings to both technical and non-technical stakeholders, ensuring that model assumptions and results are clearly understood. Collaboration may also include contributing to code reviews, sharing best practices for model validation, and mentoring colleagues on Bayesian methodologies.

What is Bayesian modeling?

Bayesian modeling is a statistical approach that uses Bayes' Theorem to update the probability of a hypothesis as more data becomes available. It incorporates prior beliefs or knowledge, combines them with observed data, and produces a posterior probability distribution to guide inference and decision-making. This approach is widely used in various fields such as machine learning, data science, and scientific research for tasks like parameter estimation, prediction, and model selection.
What are popular job titles related to Bayesian Modeling jobs in Texas? For Bayesian Modeling jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Bayesian Modeling jobs in Texas look for? The top searched job categories for Bayesian Modeling jobs in Texas are:
What cities in Texas are hiring for Bayesian Modeling jobs? Cities in Texas with the most Bayesian Modeling job openings:
Bayesian Modeling jobs near you

Senior Data Scientist, Forecasting and Analytics

McAfee

Frisco, TX • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 9 days ago

Job description

Role Summary
We are seeking a technically strong and business-oriented Senior Data Scientist to own our forecasting and planning initiatives. With a focus on forecasting as it relates to planning and marketing analytics; this role will turn complex data into actionable insights that improve acquisition, retention, customer experience and business planning value.
The ideal candidate is highly proficient in time series and machine learning forecasting methods and equally strong at translating analytical findings into clear, engaging recommendations for business stakeholders and executives. This person should be able to work independently, frame ambiguous problems, build reliable models, and influence decisions through data-driven storytelling.
This is a hybrid role located within one of our hub locations i.e. Dallas, TX, New York, NY, San Jose, CA or Newport Beach, CA. Your will be required to come into an office on an as needed basis and work from your home office the rest of the time.
Position Details
About the role:
Forecasting & Planning
  • Ownership and maintenance of forecasting models for key marketing and business outcomes, including revenue, demand, conversion, retention, and customer value.
  • Support planning cycles by translating historical trends, seasonality, campaign activity, customer behavior, macro factors, and business assumptions into clear forecasts and scenarios.
  • Develop planning tools, models, and readouts that help stakeholders and executives understand expected performance, pacing, and business tradeoffs.
  • Monitor forecast accuracy, diagnose variance versus plan, and recommend adjustments based on changing business conditions.

Advanced Analytics & Machine Learning
  • Develop and validate data science models that support customer behavior analysis, segmentation, propensity modeling, churn/retention analysis, personalization, and lifetime value.
  • Build analytical frameworks that help stakeholders understand customer needs, behavior drivers, performance trends, and areas for improvement.

Marketing Insights & Stakeholder Storytelling
  • Partner with Marketing, Finance, Product, Analytics, and Data Engineering teams to define business questions, analytical approaches, data requirements, and success metrics.
  • Translate complex model outputs into clear recommendations that help stakeholders understand what happened, why it happened, and what actions to take.
  • Communicate insights through compelling presentations, dashboards, and executive-ready readouts tailored to executive and other potentially non-technical audiences.
  • Proactively identify insights, risks, and opportunities in the data rather than waiting for narrowly defined requests.

About you:
  • 7+ yrs experience applying data science, machine learning, forecasting and/or other advanced analytics in a business environment.
  • Strong proficiency in Python, SQL, and common data science or statistical modeling libraries.
  • Strong working knowledge of time-series analysis, forecasting, seasonality, trend, lag effects, scenario planning, and model backtesting.
  • Experience with marketing analytics, customer analytics, campaign performance, acquisition, retention, conversion, or lifetime value analysis.
  • Ability to translate ambiguous business questions into structured analytical plans and actionable recommendations.
  • Strong communication and data storytelling skills, with the ability to influence marketing and business stakeholders.

Preferred Qualifications
  • Master's degree or PhD in a quantitative discipline.
  • Experience with customer lifecycle analytics, journey analytics, subscription analytics, ecommerce, SaaS, or consumer digital businesses.
  • Familiarity with experimentation, causal inference, uplift modeling, survival analysis, Bayesian modeling, or personalization methods.
  • Experience working with large-scale customer, behavioral, clickstream, campaign, planning, or transaction-level datasets.
  • Experience using cloud data platforms such as Databricks, Snowflake, BigQuery, or similar environments.
  • Experience creating executive-ready presentations that connect analytical findings to business strategy and operational decisions.

#LI-Hybrid
Company Overview
McAfee is a leader in personal security for consumers. Focused on protecting people, not just devices, McAfee consumer solutions adapt to users' needs in an always online world, empowering them to live securely through integrated, intuitive solutions that protects their families and communities with the right security at the right moment.
Company Benefits and Perks
We work hard to embrace diversity and inclusion and encourage everyone at McAfee to bring their authentic selves to work every day. We offer a variety of social programs, flexible work hours and family-friendly benefits to all of our employees.:
  • Bonus Program
  • 401k Retirement
  • Medical, Dental, Vision, Basic Life, Short Term Disability and Long-Term Disability Coverage
  • Paid Parental Leave
  • Support and Community Involvement
  • 14 Paid Company Holidays
  • Unlimited Paid Time Off for Exempt Employees
  • 96 Hours of Sick Time and 120 Hours of Vacation for Non-Exempt Employees Accrued Each Year

We're serious about our commitment to diversity which is why McAfee prohibits discrimination based on race, color, religion, gender, national origin, age, disability, veteran status, marital status, pregnancy, gender expression or identity, sexual orientation or any other legally protected status.
Pay Range
The anticipated compensation for this position is USD $107,430.00/Yr. - USD $176,490.00/Yr. depending on experience and qualifications.
Job Applicant Privacy Notice
Please click here to view and download the Job Applicant Privacy Notice, which applies to all McAfee job applicants who are residents of the state of California.

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