About DataAnnotation
Sourced by ZipRecruiter
Industry
Computing infrastructure providers, data processing, web hosting and data services
Company size
10,000+ Employees
Headquarters location
New York, NY, US
Job description
Overview Data Scientist role at DataAnnotation. You will train AI models, measure progress of AI chatbots, evaluate their logic, and solve problems to improve model quality. Responsibilities Give AI chatbots writing and editing tasks and evaluate their outputs Evaluate the quality produced by AI models for correctness and performance Qualifications Fluency in English (native or bilingual level) Detail-oriented Demonstrated proficiency in related technical, statistical, and mathematical skills A current, in progress, or completed Masters and/or PhD is preferred but not required Benefits This is a full-time or part-time REMOTE position You'll be able to choose which projects you want to work on You can work on your own schedule Projects are paid hourly starting at $40+ USD per hour, with bonuses on high-quality and high-volume work Notes Payment is made via PayPal.
We will never ask for money. PayPal handles currency conversions from USD. Only applicants in the United States will be considered for this role.
This is an independent contract position. Job details Seniority level: Entry level Employment type: Full-time Job function: Engineering and Information Technology Industries: Software Development #J-18808-Ljbffr
dataannotation.tech
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.
