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Bayesian Modeling Jobs in New York (NOW HIRING)

Meta

Competitive Intelligence Lead

New York, NY · On-site

$177K/yr

... e.g., bayesian pooling, hierarchical modeling) * Demonstrated communication skills and experience presenting complex findings to both technical and non-technical stakeholders * Demonstrated ...

Oxman

Computational Ecologist

New York, NY · On-site

$152K - $203K/yr

Strong foundation in modeling techniques (e.g., differential equations, agent-based modeling, network models, Bayesian approaches) for simulating ecological processes or population dynamics.

Chris Baily

Marketing Data Scientist

Manhattan, NY · On-site

$113K - $170K/yr

Build, validate, and improve MMM frameworks using both Bayesian and Frequentist methodologies. * Manage multiple modeling engagements simultaneously across a diverse portfolio of clients and ...

Dentsu, Inc.

Marketing Data Scientist

New York, NY · On-site

$113K - $170K/yr

Build, validate, and improve MMM frameworks using both Bayesian and Frequentist methodologies . * Manage multiple modeling engagements simultaneously across a diverse portfolio of clients and ...

The Bronx

Senior AI Data Scientist

Manhattan, NY · On-site

$220K/yr

Develop predictive and custom machine learning models using statistical, causal inference, Bayesian, and other practical algorithmic approaches. * Build AI capabilities using retrieval-augmented ...

CyberCoders

Data Scientist

New York, NY · On-site

You love building mathematical and probabilistic models, computer science algorithms, and you have ... Experience with statistical methods and analysis such as bias vs. variance tradeoffs, Bayesian ...

CyberCoders

Data Scientist

New York, NY · On-site

You love building mathematical and probabilistic models, computer science algorithms, and you have ... Experience with statistical methods and analysis such as bias vs. variance tradeoffs, Bayesian ...

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Bayesian Modeling information

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.

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 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.

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 popular job titles related to Bayesian Modeling jobs in New York?

For Bayesian Modeling jobs in New York, the most frequently searched job titles are:

What job categories do people searching Bayesian Modeling jobs in New York look for?

The top searched job categories for Bayesian Modeling jobs in New York are:

What cities in New York are hiring for Bayesian Modeling jobs?

Cities in New York with the most Bayesian Modeling job openings:

Bayesian Modeling jobs near you
Infographic showing various Bayesian Modeling job openings in New York as of September 2026, with employment types broken down into 1% Internship, 84% Full Time, 13% Part Time, and 2% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution.

Competitive Intelligence Lead

New York, NY • On-site

Meta
Internet and IT • 10K+ employees
Learn more about Metaexternal

$177K/yr

Full-time

Re-posted 8 days ago

Key responsibilities

  • Lead major projects and product areas by conducting advanced analyses, developing statistical models, and delivering actionable insights.

  • Identify, onboard, and evaluate third-party datasets to determine their predictive power and synthesize multiple data sources into high-fidelity trend reports.

  • Apply advanced statistical and causal inference methods to analyze market data, interpret market trends, and inform product and business strategies.

Meta rating

7.8

Company rating: 7.8 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

Job description

As a Competitive Intelligence Lead in Meta’s Competitive Intelligence organization, you will operate at the intersection of advanced analytics, data science, and market strategy. You will lead major projects and product areas—often in environments of significant ambiguity or technical complexity—driving both technical and business outcomes. This is a hands-on, high-impact role for builders who thrive on solving real problems. This role demands a unique blend of analytical and statistical expertise, strategic thinking , and the ability to translate complex insights into impactful product and business decisions. You will be recognized as a thought partner by cross-functional leads and will help shape the analytical foundations that inform how we build and grow our products.
Competitive Intelligence Lead Responsibilities:
  • Market Strategy: Influence organization-level product direction through data-driven narratives and an in depth understanding of the market landscape. Demonstrated experience operating at scale, and across ambiguous, environments with working knowledge of econometrics. As a quantitative market-strategist, you will blend practical and applied understanding with technical expertise, including pressure-testing data for quality, reliability, understanding data-biases and being solution driven
  • Analytics Leadership: Conduct advanced analyses with 3P datasets, develop statistical models and forecasts, and deliver actionable insights that informs market and business strategy. These include, but are not limited to:
  • Data onboarding: Identify, onboard, and rigorously evaluate 3P datasets to determine their signal-to-noise ratio and predictive power
  • Data triangulation: Triangulate data from many sources of imperfect information. Synthesize multiple, low-fidelity 3rd-party signals into a single high-fidelity trend report using Bayesian aggregation or other methods
  • Data transformation: Apply quasi-experimental designs (e.g., synthetic control, diff-in-diff) to isolate the impact of exogenous market shocks and competitor actions on internal performance metrics, using 3rd-party behavioral and economic datasets
  • Insight and implications: Apply guidance from such analyses to increase the accuracy of forecasts and better understand market trends
  • Technical & Methodological Expertise: Act as a recognized professional in a technical or methodological area (e.g., causal inference, bayesian aggregation), driving the adoption of advanced methods and organization-wide best practices that raise the bar for the entire team
  • Data Governance & Quality: Ensure data privacy, security, and compliance with organizational standards. Champion data quality frameworks and documentation practices that enable credible reproducible analyses
  • Resourceful, adaptable professional with a bias for action

Minimum Qualifications:
  • Bachelors degree and a minimum of 6 years of work experience (minimum of 4 years with a Ph.D.) in business intelligence, product analytics, or economic or strategy consulting in a technology environment with increasing scope and impact
  • Demonstrated skill to ethically source, validate, and synthesize high-signal insights from people (e.g., stakeholder interviews, skilled conversations, field research, and relationship-based information gathering) while maintaining high standards for privacy, consent, and integrity
  • Proficiency in AI-powered tools: Demonstrate working knowledge of Generative AI technologies (e.g., LLM and AI agents) and experience designing, prompting, and orchestrating AI systems (e.g., prompt engineering) to automate data analyses, synthesize insights, and execute multi-step analytical tasks (e.g., prompting agent to clean datasets, build visualizations)
  • Practical working understanding of data-analytics tools, and direct experience managing, analyzing, manipulating and interpreting 1P and external 3P datasets
  • Experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), and/or statistical/mathematical software (e.g., R)
  • Proven experience with statistical analysis including causal inference (e.g., randomized control trials, quasi-experimentation such as synthetic control, diff-in-diff, meta-analyses), and/or bayesian aggregation (e.g., bayesian pooling, hierarchical modeling)
  • Demonstrated communication skills and experience presenting complex findings to both technical and non-technical stakeholders
  • Demonstrated experience thriving in ambiguous environments and shape new analytics organizations or products

Preferred Qualifications:
  • Master's or Ph.D. Degree in a quantitative field such as Quantitative Economics or Political Science, Operations Research, Data Science, Computer Science, Physics, Business, or Mathematics
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$177,000/year to $247,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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