Data Scientist(s)- 100% Virtual-Mongo DB - (No Visa Referrals)

The company does not offer sponsorship for Visa candidates.. So, resumes have been forwarded, but they are not US citizens or green card holders, and therefore, they will not receive a response to their resumes. The job requires 20% travel, mostly to NYC. Ideally, candidates living in Central or Eastern Standard Time zones would be best; MST or PST will still be considered. A BS or Master's degree (with less experience) and internships to 1-3 years of experience, with experience in Python and Mango, are required,(A Must) A Major Global organisation with over 350 shore-based employees and now hiring in the USA, is seeking to add 5 more Data Scientists, and these roles are 100% virtual. 5 open jobs for Data Scientists to Senior Data Scientists. They will not sponsor visa candidates, only U.S. citizens or Green Cardholders. These jobs are building Databases for their client using Python and MongoDB 100% remote and there is 20 % travel to clients in the USA or to corporate headquarters in NYC– One of the clients is a global telecom company, and they just landed over $20 million in new contracts They will see entry-level positions (0-1 years) and 2- 3 years - Salary based on years of experience. Complete benefits package.. travel expenses, etc.. Desktops and Laptops.. Expense account As an entry-level Data Scientist with recent experience of 3 years, you will help design and deliver data-driven insights and solutions that enhance audience engagement across streaming and linear platforms. This role involves close collaboration with data scientists, engineers, analysts, and stakeholders, requiring strong technical and communication skills to develop scalable solutions. • Develop and deliver impactful analytical solutions and tools using statistical modeling, machine learning, and data science techniques to uncover audience insights and support decision-making. • Translate complex business problems into data-driven approaches by partnering with cross-functional teams and communicating findings clearly to technical and non-technical audiences. • Contribute meaningfully to project execution, including scoping, data exploration, modeling, validation, and documentation across both ad hoc and recurring workflows. • Advance the team's analytical rigor and technical standards by contributing to methodology development, peer reviews, and collaborative problem solving. • Think critically and rigorously about leveraging available data effectively to identify opportunities for deeper audience understanding and improved business outcomes, ETC.