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Remote Causal Inference Jobs in New York (NOW HIRING)

Headspace

Principal Data Scientist

New York, NY · On-site +1

Apply causal inference and statistical modeling to evaluate engagement, and long-term member ... City, NY (remote), and Seattle, WA (remote). Candidates must permanently reside in the US ...

Serotonin

Blockchain, Data Analytics (Remote)

New York, NY · On-site +1

$80K - $150K/yr

Experience with A/B testing, causal inference, and experimental design * Ability to communicate ... Remote Work Environment * Maternity/Paternity Leave $80,000 - $150,000 a year The salary range for ...

Serotonin

Blockchain, Data Analytics (Remote)

New York, NY · On-site +1

$80K - $150K/yr

Experience with A/B testing, causal inference, and experimental design * Ability to communicate ... Remote Work Environment * Maternity/Paternity Leave $80,000 - $150,000 a year The salary range for ...

Kelaca

AI Transformation Lead

Manhattan, NY · Remote

US East Coast, remote-first with travel Type: Full-time, individual contributor Travel ... Exposure to causal inference, causal AI, or advanced analytics beyond standard machine learning.

AlphaSense

Sr. Product Data Scientist

New York, NY · On-site +1

Ability to work seamlessly with a highly technical remote data team (India) while acting as the ... Use advanced statistical methods (e.g., cohort analysis, propensity matching, causal inference, etc ...

Jackpot

Director of Data & Analytics

New York, NY · On-site +1

$170K - $200K/yr

While this is a remote position, you must be located or willing to relocate to the NYC Metro area ... Experience with A/B testing frameworks, causal inference, and experimentation platforms

New

Wand

Product Data Analyst

New York, NY · Remote

$145K - $175K/yr

Causal inference methods (diff-in-diff, regression discontinuity, propensity matching) * Prior work ... Experience building metrics frameworks or KPI hierarchies from scratch How we work Fully remote ...

Junction

Data Scientist

New York, NY · On-site +1

$180K - $220K/yr

Fully remote (EST timezone only) Why we need you Junction sits in the flow of high-value ... Experience applying causal inference methods, such as diff-in-diff, propensity scoring, or ...

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Remote Causal Inference information

What is a Remote Causal Inference job?

A Remote Causal Inference job involves using statistical and analytical methods to determine cause-and-effect relationships from data, often for fields like healthcare, social sciences, or business. Professionals in this role work remotely, leveraging tools such as R, Python, or specialized software to analyze experiments, observational studies, or large datasets. Their insights help organizations make data-driven decisions, design better interventions, and accurately measure the impact of policies or treatments. Strong skills in statistics, machine learning, and communication are essential for success in this position.

What are the key skills and qualifications needed to thrive as a Remote Causal Inference Specialist, and why are they important?

To thrive as a Remote Causal Inference Specialist, you need strong quantitative and statistical skills, a solid background in econometrics or data science, and typically an advanced degree in a related field. Proficiency with statistical programming languages such as R or Python, experience with causal inference frameworks like propensity score matching or instrumental variables, and familiarity with data visualization tools are crucial. Outstanding problem-solving abilities, clear communication, and self-motivation are essential soft skills for working independently and conveying complex results to non-technical stakeholders. These skills enable accurate, actionable insights from data, which drive evidence-based decision-making in remote, collaborative environments.

How does a remote Causal Inference specialist typically collaborate with cross-functional teams, and what tools are commonly used?

As a remote Causal Inference specialist, you’ll frequently work with data scientists, product managers, and engineers to design and interpret experiments, analyze observational data, and provide actionable insights. Collaboration usually happens through regular video meetings, shared documentation, and project management tools. Commonly used platforms include Slack or Microsoft Teams for communication, GitHub for code collaboration, and Jupyter Notebooks or RMarkdown for sharing reproducible analyses. These tools help ensure transparency and maintain strong teamwork despite the remote environment.
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Remote Causal Inference jobs near you

Senior Machine Learning Engineer

SW5 Consulting

New York, NY • Remote

$180K - $250K/yr

Full-time

Re-posted yesterday

Job description

Senior Machine Learning Engineer


Location: Remote (U.S.) or New York City


Compensation: $180K – $250K + Equity


Employment Type: Full-time


About Us

We’re building cutting-edge AI solutions that help some of the world’s most recognizable brands connect with their customers in smarter, more meaningful ways. Our technology predicts who to reach, when to reach them, and through which channel—maximizing engagement and driving profitable growth.


The Role


As a Senior Machine Learning Engineer, you’ll be at the heart of our product innovation. You will:

  • Design, train, and deploy ML models that power marketing personalization at scale.
  • Build robust MLOps pipelines for training, serving, and monitoring models in production.
  • Experiment and optimize using A/B testing, uplift modeling, and causal inference.
  • Collaborate with leadership and cross-functional teams, mentoring others and shaping best practices.


What We’re Looking For

  • 5+ years in software engineering, with 3+ years in ML systems.
  • Experience with GCP, specifically in Vertex AI and / or Kubeflow
  • Expertise in modern ML algorithms (tree-based methods, deep learning, transformers).
  • Hands-on experience with PyTorch, TensorFlow, XGBoost.
  • Strong Python skills and familiarity with Spark, Ray, BigQuery, Airflow.
  • Experience with MLOps, CI/CD, containerization (Docker/Kubernetes), and cloud platforms (GCP preferred).
  • Comfort with advanced experimentation techniques and performance measurement.


Bonus Points

  • Background in marketing tech or ad tech.
  • Experience with LLMs, reinforcement learning, or bandit algorithms.
  • Familiarity with causal inference and uplift modeling.
  • Startup experience and ability to thrive in a fast-paced environment.


Why Join Us?

  • Impact: Your work will directly shape how leading brands engage millions of customers.
  • Growth: Collaborate with industry veterans and learn from the best.
  • Innovation: Experiment with cutting-edge ML models and infrastructure.
  • Culture: We value ownership, iteration, and continuous learning—your voice matters.


This role is a fully remote role but you MUST be based in US and eligible to work without sponsor. Bonus points if you can occasionally get to New York. The position will pay $200-250k + equity