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Data Science Analyst - Remote

Brentwood, TN · On-site +1

$75K - $87K/yr

This is a Full Time, remote, Data Science Analyst role. What You'll Do * Analysis, Model Development & AI Solutions: * Perform exploratory data analysis to identify patterns and opportunities in ...

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How much do remote data science startup jobs pay per year?

As of May 28, 2026, the average yearly pay for remote data science startup in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive at a remote data science startup, and why are they important?

To thrive at a remote data science startup, you need strong analytical skills, proficiency in statistics, and experience with programming languages like Python or R, often supported by a degree in data science, computer science, or a related field. Familiarity with tools such as Jupyter Notebook, SQL databases, cloud platforms (e.g., AWS, GCP), and version control systems like Git is typically required. Exceptional self-motivation, communication, and collaboration skills are crucial to excel in a remote and fast-paced startup environment. These competencies enable you to deliver actionable insights, adapt to rapid changes, and collaborate effectively across distributed teams.

What are some unique challenges of working as a data scientist at a remote startup, and how can I prepare for them?

Working as a data scientist at a remote startup often involves navigating ambiguous project requirements, rapidly shifting priorities, and a high degree of autonomy. You may find yourself balancing multiple roles, such as data engineering and analysis, especially when the team is small. Strong communication skills are essential for collaborating effectively across time zones and ensuring alignment with product and business goals. Preparing by developing self-management habits, proactively seeking feedback, and becoming comfortable with remote collaboration tools will help you thrive in this dynamic environment.

What is a Remote Data Science Startup?

A Remote Data Science Startup is a company focused on developing data-driven solutions, analytics, or products, with a team that primarily works remotely rather than from a central office. These startups leverage data science techniques such as machine learning, statistical analysis, and big data processing to solve business problems or create innovative products. Employees collaborate using digital tools and platforms, allowing for flexible work arrangements and access to a global talent pool. Remote data science startups often serve various industries, including healthcare, finance, e-commerce, and technology.
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What cities are hiring for Remote Data Science Startup jobs? Cities with the most Remote Data Science Startup job openings:
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Remote Data Science Startup jobs near you
Infographic showing various Remote Data Science Startup job openings in the United States as of May 2026, with employment types broken down into 5% Internship, 45% Full Time, 2% Part Time, and 48% Contract. Highlights an 12% Physical, and 88% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.
Remote Data Science Consultant & AI Trainer

Remote Data Science Consultant & AI Trainer

DataAnnotation

Boston, MA • 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). Note: 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. #datascience #J-18808-Ljbffr

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