ZipRecruiter

Log In

1

Causal Inference Machine Learning Postdoctoral Jobs in Newark, NJ

Walmart

(USA) Principal, Data Scientist

Hoboken, NJ · On-site

$132K - $264K/yr

This team leads advancements in generative AI, agentic intelligence, machine learning, measurement, and causal inference to redefine retail experiences, optimize operations, and develop new business ...

OpenX

Data Scientist III

New York, NY · Remote

Apply expertise across several core areas of machine learning and statistics (e.g., gradient-boosted models, deep neural networks, time series, causal inference concepts, experimentation design ...

Colgate-Palmolive

Machine Learning Engineer

Manhattan, NY · On-site

$105 - $150/hr

Overview We are seeking a Machine Learning Engineer who brings the analytical rigor of a data ... Proficient with a selection of Bayesian methods, causal inference, and/or predictive modeling ...

OpenX

Data Scientist III

New York, NY · On-site

Apply expertise across several core areas of machine learning and statistics (e.g., gradient-boosted models, deep neural networks, time series, causal inference concepts, experimentation design ...

OpenX

Data Scientist III

New York, NY · On-site

Apply expertise across several core areas of machine learning and statistics (e.g., gradient-boosted models, deep neural networks, time series, causal inference concepts, experimentation design ...

Mount Sinai Hospital

Postdoctoral Fellow-MSH

Manhattan, NY · On-site

$53K - $73K/yr

... machine-learning/deep-learning methodology research with application to biomedical data. • ... and causal-inference methodology research with application to medical/clinical-trial studies. The ...

Mount Sinai Hospital

Postdoctoral Fellow-MSH

Manhattan, NY · On-site

$53K - $73K/yr

... machine-learning/deep-learning methodology research with application to biomedical data. • ... and causal-inference methodology research with application to medical/clinical-trial studies. The ...

previous page

Showing results 41-60

All JobsCausal Inference Machine Learning Postdoctoral JobsCausal Inference Machine Learning Postdoctoral Jobs in Newark, NJ

Causal Inference Machine Learning Postdoctoral information

See Newark, NJ salary details

$37.1K

$56.7K

$63.8K

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

As of Sep 3, 2026, the average yearly pay for causal inference machine learning postdoctoral in Newark, NJ is $56,702.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,900.00 and $59,100.00 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?

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.

Is it difficult to get a causal inference machine learning postdoctoral position?

Securing a causal inference machine learning postdoctoral position can be competitive due to specialized skills required, such as expertise in statistical methods, programming (e.g., Python or R), and a strong research background. Candidates with relevant publications, strong recommendations, and experience in machine learning frameworks often have better chances, but the availability of such positions varies by institution and funding.

What are popular job titles related to Causal Inference Machine Learning Postdoctoral jobs in Newark, NJ?

For Causal Inference Machine Learning Postdoctoral jobs in Newark, NJ, the most frequently searched job titles are:

What job categories do people searching Causal Inference Machine Learning Postdoctoral jobs in Newark, NJ look for?

The top searched job categories for Causal Inference Machine Learning Postdoctoral jobs in Newark, NJ are:

What cities near Newark, NJ are hiring for Causal Inference Machine Learning Postdoctoral jobs?

Cities near Newark, NJ with the most Causal Inference Machine Learning Postdoctoral job openings:

Causal Inference Machine Learning Postdoctoral jobs near you

Quantitative Researcher, Central Execution Desk

Tower Research Capital

New York, NY • On-site

$120K - $200K/yr

Full-time

PTO

Re-posted 7 hours ago

Job description

Tower Research Capital is a leading quantitative trading firm founded in 1998. Tower has built its business on a high-performance platform and independent trading teams. We have a 25+ year track record of innovation and a reputation for discovering unique market opportunities.
Tower is home to some of the world's best systematic trading and engineering talent. We empower portfolio managers to build their teams and strategies independently while providing the economies of scale that come from a large, global organization.
Engineers thrive at Tower while developing electronic trading infrastructure at a world class level. Our engineers solve challenging problems in the realms of low-latency programming, FPGA technology, hardware acceleration and machine learning. Our ongoing investment in top engineering talent and technology ensures our platform remains unmatched in terms of functionality, scalability and performance.
At Tower, every employee plays a role in our success. Our Business Support teams are essential to building and maintaining the platform that powers everything we do - combining market access, data, compute, and research infrastructure with risk management, compliance, and a full suite of business services. Our Business Support teams enable our trading and engineering teams to perform at their best.
At Tower, employees will find a stimulating, results-oriented environment where highly intelligent and motivated colleagues inspire each other to reach their greatest potential.
The Central Execution Desk is looking for a Quantitative Researcher to build models, analytics, and decision systems that improve execution quality across global trading teams. The role sits at the intersection of market impact research, transaction cost analysis, causal inference, experiment design, optimization, and execution strategy.
The researcher will work on understanding and improving how orders are routed, scheduled, evaluated, and optimized across brokers, algorithms, venues, markets, and trading teams. The work will combine rigorous quantitative research with practical execution-desk decision support, including market impact modeling, slippage analysis, causal inference, algo selection, broker evaluation, venue toxicity, A/B testing, and optimization under execution risk.
Responsibilities
  • Researching market impact, execution cost, slippage, fill quality, etc. across global markets
  • Building models to explain and predict execution outcomes
  • Designing and analyzing A/B experiments to identify real execution improvements
  • Working on causal inference methods
  • Developing optimization models for various execution objectives
  • Supporting research into centralized inventory, liquidity, risk-transfer, and crossing-style analytics to improve portfolio-level execution outcomes
  • Contributing to research on execution algorithms
  • Building research tools, simulations, dashboards, and reports that help traders and PMs make better execution decisions
  • Partnering with traders, PMs, quant developers, and engineers to turn research prototypes into robust production analytics.
Qualifications
  • A Masters or Bachelors from a top-tier university in mathematics, statistics, computer science, financial engineering, physics, operations research, or a related quantitative field. PhD preferred
  • At least 2-5 years of quantitative research experience, ideally in execution research, market microstructure, or financial data modeling
  • Strong knowledge of statistics, time-series analysis, experiment design, optimization, machine learning, and financial markets
  • Experience working with large financial datasets
  • Strong Python skills for research, data analysis, modeling, and simulation. C++/Rust experience is a plus but not required
  • Familiarity with convex optimization, causal inference, market impact models, stochastic control is a plus
  • Good understanding of market microstructure
  • Ability to write clear research notes and explain quantitative results to traders, PMs, and engineers. Prior academic publications or comparable research writing are a plus

Anticipated annual base salary range $120,000 - $200,000, plus eligible for discretionary bonus.
Benefits
Tower's headquarters are in the historic Equitable Building, right in the heart of NYC's Financial District and our impact is global, with over a dozen offices around the world.
At Tower, we believe work should be both challenging and enjoyable. That is why we foster a culture where smart, driven people thrive - without the egos. Our open concept workplace, casual dress code, and well-stocked kitchens reflect the value we place on a friendly, collaborative environment where everyone is respected, and great ideas win.
Our benefits include:
  • Generous paid time off policies
  • Savings plans and other financial wellness tools available in each region
  • Hybrid working opportunities
  • Free breakfast, lunch, and snacks daily
  • In-office wellness experiences and reimbursement for select wellness expenses (e.g., gym, personal training and more)
  • Company-sponsored sports teams and fitness events (JPM Corporate Challenge, Cycle for Survival, Wall Street Rides FAR and more)
  • Volunteer opportunities and charitable giving
  • Social events, happy hours, treats, and celebrations throughout the year
  • Workshops and continuous learning opportunities

At Tower, you'll find a collaborative and welcoming culture, a diverse team and a workplace that values both performance and enjoyment. No unnecessary hierarchy. No ego. Just great people doing great work - together.
Tower Research Capital is an equal opportunity employer.

Apply