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Remote Phd Statistics Jobs in Missouri (NOW HIRING)

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New ... Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus.

... skills in Statistics and/or Computer Science. Benefits This is a full-time or part-time REMOTE ... or PhD is preferred but not required Notes Payment is made via PayPal. We will never ask for any ...

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Remote Phd Statistics information

What are the key skills and qualifications needed to thrive as a Remote PhD Statistician, and why are they important?

To thrive as a Remote PhD Statistician, you need advanced statistical knowledge, expertise in data analysis, and a doctoral degree in statistics or a related field. Proficiency in statistical software such as R, SAS, or Python, and experience with data management systems are typically required. Strong problem-solving abilities, self-motivation, and effective written communication are crucial for collaborating remotely and presenting complex findings clearly. These skills ensure rigorous data analysis, reliable insights, and effective contributions to research or business objectives in a remote environment.

What are some common challenges faced by remote PhD statisticians, and how can they be addressed?

Remote PhD statisticians often face challenges such as maintaining clear communication with cross-functional teams, managing time across different time zones, and staying updated with the latest statistical methodologies. These can be addressed by leveraging collaborative tools (like Slack or Zoom), setting regular check-ins with team members, and participating in virtual conferences or workshops. Proactively seeking feedback and documenting work processes also helps ensure alignment and productivity in a remote environment.

What are remote PhD statistics jobs?

Remote PhD statistics jobs are positions that require an advanced degree (PhD) in statistics, allowing professionals to work from home or any location outside a traditional office. These roles typically involve designing statistical models, analyzing complex data sets, and collaborating with research teams or organizations virtually. Common industries hiring for remote PhD statistics jobs include academia, healthcare, pharmaceuticals, tech, and government agencies. The flexibility of remote work enables statisticians to contribute to projects worldwide while maintaining a work-life balance.

What is the difference between Remote Phd Statistics vs Remote Data Scientist?

AspectRemote Phd StatisticsRemote Data Scientist
Required CredentialsPhD in Statistics or related fieldBachelor's or Master's in Data Science, Statistics, or related field
Work EnvironmentResearch-focused, often academic or industry R&DApplied analytics, product development, business insights
Employer & Industry UsageUniversities, research institutions, biotech, financeTech companies, finance, healthcare, e-commerce
Common Search & ComparisonYesYes

Remote Phd Statistics roles typically involve research, advanced statistical modeling, and theoretical work, often in academic or R&D settings. Remote Data Scientist positions focus on applying data analysis, machine learning, and programming skills to solve practical business problems. While both roles require strong analytical skills, the PhD in Statistics emphasizes research and theory, whereas Data Scientists focus on application and implementation.

What are the most commonly searched types of Phd Statistics jobs in Missouri? The most popular types of Phd Statistics jobs in Missouri are:
What cities in Missouri are hiring for Remote Phd Statistics jobs? Cities in Missouri with the most Remote Phd Statistics job openings:
Survey Statistician - AI Trainer

Survey Statistician - AI Trainer

DataAnnotation

Kansas City, MO • On-site, Remote

$60/hr

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

Join the DataAnnotation team and contribute to developing cutting‐edge AI systems, while enjoying the flexibility of remote work and setting your own schedule. We are looking for experienced quantitative professionals to help advance AI development. AI models are increasingly capable of performing complex analytical and scientific reasoning — but these systems still need practitioners with real‐world quantitative experience to validate whether the outputs actually hold up in practice.

That's where you come in. As a member of DataAnnotation's team, you'll work closely with state‐of‐the‐art AI models on tasks like evaluating AI‐generated quantitative analysis, solving technical problems, and providing feedback that directly shapes how these systems reason about data, models, and scientific problems. Whether your background is in data science, astrophysics, economics, biostatistics, operations research, or any other quantitative field, if you think rigorously about data and models, your skills are directly applicable here.

Some team members fit this work alongside a full‐time role, while others treat it as their primary focus. To get started, once you sign up for an account, you'll take a short assessment (this serves as our version of an interview). If you pass, you'll receive an email confirmation, and paid work will become available on our platform.

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand. Flexible schedule: choose which projects you take on and when you work. Competitive pay: projects are paid hourly, up to $60 USD/hour.

Impact: help shape the future of AI systems built to reason about data and analytics. Responsibilities Evaluate AI‐generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data‐driven insights, for technical accuracy and real‐world validity. Design and solve quantitative problems used to train and benchmark AI systems, spanning areas like forecasting, experimental analysis, optimization, and statistical inference.

Write clear technical explanations and well‐documented analytical code. Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning. Qualifications 2+ years of hands‐on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or any adjacent field.

Some coding experience required, with comfort writing and reviewing analytical code end‐to‐end. Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time‐series forecasting). Fluency in English (native or bilingual level) with strong writing skills.

A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus. Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise). Payment is made via PayPal.

We will never ask for any money from you. This job is only available to those in the US, Canada, UK, Ireland, Australia, and New Zealand. #J-18808-Ljbffr