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Causal Inference Machine Learning Postdoctoral Jobs in Margate, FL

Chewy

Associate Director Product Manager

Plantation, FL

$166K - $265K/yr

In this role, you will own the product roadmap for Pricing Data Science, Machine Learning, and AI ... Experience with experimentation, A/B testing, causal inference, measurement design, or model ...

Varsity Tutors

LSAT Logical Reasoning Tutor

Cooper City, FL · Remote

$26 - $40/hr

... inference questions. Ability to explain argument structure, conditional logic, causal reasoning ... Ability to adapt to different learning styles and student needs. Ways To Connect With Students * 1 ...

Varsity Tutors

LSAT Logical Reasoning Tutor

Sunrise, FL · Remote

$26 - $40/hr

... inference questions. Ability to explain argument structure, conditional logic, causal reasoning ... Ability to adapt to different learning styles and student needs. Ways To Connect With Students * 1 ...

Varsity Tutors

LSAT Logical Reasoning Tutor

Miramar, FL · Remote

$26 - $40/hr

... inference questions. Ability to explain argument structure, conditional logic, causal reasoning ... Ability to adapt to different learning styles and student needs. Ways To Connect With Students * 1 ...

Varsity Tutors

LSAT Logical Reasoning Tutor

Hialeah, FL · Remote

$26 - $40/hr

... inference questions. Ability to explain argument structure, conditional logic, causal reasoning ... Ability to adapt to different learning styles and student needs. Ways To Connect With Students * 1 ...

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All JobsCausal Inference Machine Learning Postdoctoral JobsCausal Inference Machine Learning Postdoctoral Jobs in Margate, FL

Causal Inference Machine Learning Postdoctoral information

See Margate, FL salary details

$32.1K

$49K

$55.2K

How much do causal inference machine learning postdoctoral jobs pay per year?

As of Jul 14, 2026, the average yearly pay for causal inference machine learning postdoctoral in Margate, FL is $49,029.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,400.00 and $51,100.00 per year, depending on experience, location, and employer.

What is a Causal Inference Machine Learning Postdoctoral researcher?

A Causal Inference Machine Learning Postdoctoral researcher is a scientist who specializes in developing and applying machine learning methods to understand cause-and-effect relationships in data. They typically hold a recent PhD in statistics, computer science, economics, or a related field, and work in academic or industry research settings. Their work involves designing experiments, analyzing complex datasets, and creating models that can infer causal relationships, which are crucial for making robust predictions and informed decisions. This role often collaborates with interdisciplinary teams to apply these techniques to domains such as healthcare, social science, or economics.

What are the key skills and qualifications needed to thrive as a Causal Inference Machine Learning Postdoctoral researcher, and why are they important?

To thrive as a Causal Inference Machine Learning Postdoctoral researcher, you need a strong background in statistics, causal inference methodologies, and advanced machine learning, usually evidenced by a PhD in a relevant field. Familiarity with programming languages such as Python or R, experience using statistical software (e.g., TensorFlow, PyTorch, Stan), and knowledge of causal inference libraries are typically required. Outstanding analytical thinking, problem-solving abilities, and strong communication skills help you collaborate effectively and explain complex concepts to diverse audiences. These skills and qualifications are vital for advancing research, deriving actionable insights from data, and contributing to impactful scientific discoveries.

What are some common challenges faced by Causal Inference Machine Learning Postdoctoral researchers when integrating causal models with real-world data?

Causal Inference Machine Learning Postdoctoral researchers often encounter challenges such as dealing with unobserved confounding variables, ensuring data quality, and addressing biases inherent in observational datasets. Integrating advanced machine learning techniques with causal inference frameworks requires careful consideration of model assumptions and validation methods. Collaboration with domain experts is essential to properly interpret results and to translate findings into actionable insights, especially in interdisciplinary settings like healthcare or social sciences.

What is the difference between Causal Inference Machine Learning Postdoctoral vs Data Scientist?

AspectCausal Inference Machine Learning PostdoctoralData Scientist
Required CredentialsPhD in statistics, machine learning, or related fieldBachelor's or Master's in data science, computer science, or related field
Work EnvironmentAcademic research, research labs, universitiesCorporate, tech companies, startups
Industry UsageResearch, academia, specialized industry projectsBusiness analytics, product development, data-driven decision making
Common Search/ComparisonYesYes

The main difference is that Causal Inference Machine Learning Postdoctoral roles focus on academic research and developing new methods in causal inference, often requiring a PhD. Data Scientists typically work in industry, applying existing models to solve business problems, with a focus on data analysis and visualization. While both roles involve machine learning, the postdoctoral position emphasizes research and theory, whereas data science emphasizes practical application.

What cities near Margate, FL are hiring for Causal Inference Machine Learning Postdoctoral jobs? Cities near Margate, FL with the most Causal Inference Machine Learning Postdoctoral job openings:
Causal Inference Machine Learning Postdoctoral jobs near you
Senior Data Scientist

Senior Data Scientist

Haystack News

Fort Lauderdale, FL • On-site

Full-time

Re-posted 27 days ago

Job description

Haystack News, the number one destination for news on streaming platforms, is looking for a Sr Data Scientist to join our team. Haystack is trusted by over 30 million viewers and is among the fastest-growing TV news companies in the world.
Join our team at Haystack News as a Senior Data Scientist and become a pivotal force in redefining user experiences through cutting-edge algorithm enhancements. In this role, you'll leverage your advanced statistical analysis, modeling, causal inference, experimental design (A/B testing) and data analytics expertise to drive substantial improvements in user engagement and retention, directly impacting our product's success. This is an exceptional opportunity to showcase your robust problem-solving capabilities and to thrive in a collaborative environment, working alongside a team of passionate professionals dedicated to innovation and excellence. Be part of a dynamic workplace where your contributions make a meaningful difference and help shape the future of news consumption.
MINIMUM QUALIFICATIONS
  • PhD or M.S. in Computer Science, Mathematics, Electrical Engineering, Statistics, Economics or Operations Research with 5+ years of professional experience in data science, machine learning or related quantitative field
  • 3+ years of professional experience with large-scale online ranking/recommender systems (for news feeds, shopping, ads, music, etc).
  • Deep expertise in statistical inference and experimental design: hypothesis testing, power/sample size calculations, variance reduction, etc.
  • Proficiency in causal inference methods to measure product impact.
  • Proven ability to translate offline analysis into product decisions and measurable improvements in online metrics.
  • Fluency in the Python analytics stack (pandas, NumPy), statistical modeling (statsmodels or scikit-learn) and machine learning packages such as LightGBM and XGBoost.
  • Strong experience with SQL (e.g. postgres, snowflake, etc).

PREFERRED QUALIFICATIONS:
  • Experience working on consumer-facing products with millions of users.
  • Hands-on experience with orchestration/transformation tools (e.g. dbt and Airflow).
  • Experience with deep learning and being familiar with tools such as PyTorch or TensorFlow.
  • Hands-on development of products/tools incorporating GenAI, LLMs, RAG, and/or Agents.

RESPONSIBILITIES
  • Build statistical and machine learning models to improve content discovery and user engagement.
  • Work closely with ML engineers to translate models and insights into production systems.
  • Have curiosity and apply analytical skills to dive deep into data to find key insights that would impact the business.
  • Apply causal inference methods to understand the impact of potential product changes.
  • Define and build new ML features using text and multimodal embeddings and GenAI.
  • Validate offline learnings with online outcomes through AB testing. Design, execute, and analyze experiments to prove product change attribution.

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