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Postdoctoral In Bayesian Statistics Jobs in Washington

Meta

Competitive Intelligence Research

Washington, DC

$177K/yr

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 ...

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Postdoctoral In Bayesian Statistics information

What is a Postdoctoral position in Bayesian Statistics?

A Postdoctoral position in Bayesian Statistics is a research-focused role for individuals who have recently completed their PhD in statistics, mathematics, or a related field. These positions involve conducting advanced research using Bayesian methods, which apply probability to infer statistical conclusions. Postdocs often work on developing new Bayesian models, collaborating on interdisciplinary projects, and publishing research findings. Such positions are typically temporary and designed to further prepare researchers for academic, industry, or governmental roles.

What are some common challenges faced by postdoctoral researchers in Bayesian statistics, and how can they be addressed?

Postdoctoral researchers in Bayesian statistics often encounter challenges such as managing complex, high-dimensional data, staying current with rapidly evolving computational methods, and balancing independent research with collaborative projects. Effective strategies include leveraging open-source statistical software, actively participating in seminars and workshops to stay updated, and establishing regular communication with interdisciplinary teams. Building a strong professional network and seeking mentorship within the department can also help in navigating research obstacles and advancing one's career.

What is the difference between Postdoctoral In Bayesian Statistics vs Postdoctoral In Data Science?

AspectPostdoctoral In Bayesian StatisticsPostdoctoral In Data Science
Required CredentialsPhD in Statistics, Mathematics, or related fieldPhD in Computer Science, Statistics, or related field
Work EnvironmentAcademic research, university labsResearch institutions, tech companies, industry labs
Employer & Industry UsageUniversities, research institutesTech firms, finance, healthcare, consulting
Common Search & Comparison IntentSpecialized research roles in Bayesian methodsBroader data analysis and machine learning roles

Postdoctoral In Bayesian Statistics focuses on advanced research in Bayesian methods within academic settings, requiring deep statistical expertise. In contrast, Postdoctoral In Data Science covers a broader range of data analysis techniques, including machine learning, often in industry environments. Both roles require a PhD but differ in application focus and work environment.

What are the key skills and qualifications needed to thrive as a Postdoctoral Researcher in Bayesian Statistics, and why are they important?

To thrive as a Postdoctoral Researcher in Bayesian Statistics, you need an advanced degree (typically a PhD) in statistics or a related field, with strong expertise in Bayesian inference and probabilistic modeling. Proficiency with statistical programming languages such as R, Python, or Stan, and experience with specialized Bayesian analysis software are highly valued. Excellent problem-solving skills, collaboration, and the ability to communicate complex statistical concepts clearly are standout soft skills for this role. These skills and qualities are crucial for conducting rigorous research, publishing impactful results, and contributing effectively to scientific teams.
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Competitive Intelligence Research

Competitive Intelligence Research

Meta

Washington, DC

$177K/yr

Full-time

Posted 17 days ago

Meta rating

7.5

Company rating: 7.5 out of 10

Based on 43 frontline employees who took The Breakroom Quiz

123rd of 191 rated software companies

Job description

As a Senior Analyst 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 Research 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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