Top Remote Data Science Jobs in Memphis, TN

Lead a data-driven Marketing program using quantitative data and technology to attract and retain users. Manage a team of marketing data scientists and collaborate with various departments to drive corporate reporting and planning.

Design and implement solutions using statistical methods and machine learning to address complex business questions. Collaborate with teams to obtain relevant datasets, create models, and oversee scalable codebases. Drive decision-making through data insights in a healthcare technology environment.

Senior Data Scientist role in marketing, leveraging analytics techniques to optimize marketing campaigns, analyze user behaviors, and drive business growth for a SaaS company.

Join our team as a Senior Data Scientist in Fraud Risk, responsible for identifying and preventing fraud and credit risks using analytical skills and machine learning solutions. Collaborate with various teams to influence the global Risk roadmap and processes, and contribute to Square's Banking initiatives.

The Sr Prin, Content Development - Environmental Health and Safety role at Skillsoft involves serving as an in-house workplace safety and health expert, supporting the global sales force in positioning the ESH Compliance Solution. Responsibilities include interacting with C-level executives, maintaining expertise on US and international laws, enhancing Skillsoft's position as a thought leader, and developing new sales and marketing strategies.

Establish Pie as the preeminent commercial insurance among small business owners through data-driven AI/ML solutions. Conceptualize, build, and enhance AI/ML solutions for risk and underwriting challenges. Develop new features, automate capabilities, and showcase AI-ML capabilities to leadership and peers.

As a Decision Scientist, you will apply data-driven techniques to identify opportunities, participate in project definition, and directly impact business strategy setting outcomes. You will be responsible for implementing and monitoring customer-facing decisions and risk controls, as well as working closely with ML teams to inform model evaluations.