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Remote Data Science Physics Jobs in Springfield, MA

DataAnnotation

Data Science Consultant

Hartford, CT · On-site +1

$60/hr

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New ... as data science, statistics, economics, finance, physics, biology, epidemiology, operations ...

The Hartford

Director of Data Science

Hartford, CT · On-site +1

$153.20K - $229.80K/yr

Dir Data Science - GD06AE We're determined to make a difference and are proud to be an insurance ... Candidates who do not live near an office may be considered for a remote work arrangement with ...

The Hartford

Data Scientist

Hartford, CT · On-site +1

$90.16K - $135.24K/yr

... science team responsible for designing and delivering powerful analytical insights utilizing ... This role can have a Hybrid or Remote work arrangement depending on experience and skillset.

DataAnnotation

Physicist - AI Trainer

Hartford, CT · On-site +1

$60/hr

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New ... as data science, statistics, economics, finance, physics, biology, epidemiology, operations ...

DataAnnotation

Growth Analyst - AI Trainer

Hartford, CT · On-site +1

$40/hr

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New ... as data science, statistics, economics, finance, physics, biology, epidemiology, operations ...

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Remote Data Science Physics information

What are the key skills and qualifications needed to thrive as a Remote Data Science Physicist, and why are they important?

To thrive as a Remote Data Science Physicist, you need a strong background in physics, statistics, and mathematics, typically supported by a relevant degree (such as Physics or Data Science) and experience with data analysis. Proficiency with programming languages like Python or R, machine learning frameworks, and data visualization tools is essential, along with familiarity with cloud-based collaboration platforms. Excellent problem-solving skills, communication, and self-motivation are crucial soft skills for remote work and interdisciplinary collaboration. These skills ensure accurate data-driven insights, effective teamwork, and successful project delivery in a remote environment.

How do remote data science physicists typically collaborate with multidisciplinary teams despite working offsite?

Remote data science physicists often work closely with software engineers, domain scientists, and project managers through virtual collaboration tools such as Slack, Zoom, and cloud-based platforms for data sharing and analysis. Regular online meetings, shared documentation, and version-controlled repositories (like GitHub) are essential for maintaining clear communication and workflow alignment. While remote work offers flexibility, it requires proactive communication and strong organizational skills to ensure seamless integration with the broader research or product development team.

What is a Remote Data Science Physics job?

A Remote Data Science Physics job involves using data science tools, such as statistical analysis, machine learning, and programming, to solve problems or analyze data related to physics, all while working from a remote location. Professionals in this field may work on projects like simulations, data modeling, or research for academic or industry settings. They apply their understanding of physics concepts alongside data science skills to extract meaningful insights from large and complex datasets. This role often requires proficiency in programming languages like Python or R, knowledge of data analysis techniques, and a strong foundation in physics.

What is the difference between Remote Data Science Physics vs Remote Data Science Engineering?

AspectRemote Data Science PhysicsRemote Data Science Engineering
Required CredentialsPhysics degree, data science certificationsEngineering degree, data science certifications
Work EnvironmentResearch labs, tech companies, academiaTech firms, manufacturing, software companies
Industry UsageScientific research, academia, tech innovationProduct development, systems engineering, software solutions

Remote Data Science Physics focuses on applying physics principles to data analysis and modeling, often in research or scientific contexts. Remote Data Science Engineering emphasizes developing data-driven products and systems within engineering and technology sectors. While both roles require data science skills, their industry applications and focus areas differ significantly.

What are popular job titles related to Remote Data Science Physics jobs in Springfield, MA? For Remote Data Science Physics jobs in Springfield, MA, the most frequently searched job titles are:
What job categories do people searching Remote Data Science Physics jobs in Springfield, MA look for? The top searched job categories for Remote Data Science Physics jobs in Springfield, MA are:
What cities near Springfield, MA are hiring for Remote Data Science Physics jobs? Cities near Springfield, MA with the most Remote Data Science Physics job openings:
Remote Data Science Physics jobs near you
Data Science Consultant

Data Science Consultant

DataAnnotation

Hartford, CT • 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

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