Data Science Consultant

Data Science Consultant

DataAnnotation

Santa Fe, NM • On-site, Remote

$40/hr

Full-time

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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, starting at $40+ USD per 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




Frequently asked questions

Q: What skills or qualities help someone succeed as a Data Scientist?

A: To succeed as a Data Scientist, one must possess core technical skills such as proficiency in programming languages like Python, R, or SQL, as well as expertise in machine learning algorithms, data visualization tools like Tableau or Power BI, and statistical modeling techniques. Additionally, strong soft skills like effective communication, collaboration, and problem-solving abilities, along with traits like curiosity, adaptability, and attention to detail, are crucial for success in this role. By combining these technical and soft skills, Data Scientists can effectively extract insights from complex data, drive business decisions, and drive career growth through continuous learning and innovation.

Q: What is the career path for a Data Scientist?

A: A Data Scientist's typical career progression involves starting as a Junior Data Analyst or Data Scientist, where they develop foundational skills in data analysis, machine learning, and visualization. As they gain experience, they can move into mid-level roles such as Senior Data Scientist or Lead Data Analyst, where they take on more complex projects, mentor junior team members, and contribute to strategic decision-making. Ultimately, senior Data Scientists can transition into leadership positions like Director of Data Science or Chief Data Officer, or pursue specialized roles like Data Engineering or Artificial Intelligence Research Scientist, depending on their interests and skills.



DataAnnotation job posting for a Data Science Consultant in Santa Fe, NM with a salary of $40 Hourly with a map of Santa Fe location.