Responsibilities:

• Collaborate with Data Scientists, Engineers, Product Managers, and Sales team to translate business opportunities into data science use cases, and turn projects into products.
• Write prototype and production-level code and team up with Engineering to implement algorithms in production.
• Conduct research and science related activities such as, but not limited to: exploratory data analysis, statistical / machine learning / deep learning model development, model testing and validation.
• Utilize commonly used database (i.e. SQL based) and computing (e.g. notebooks) environments to process data and implement a working prototype of the desired solution.
• Learn and apply new methodologies in the intersection of applied mathematics / probability / statistics / machine learning / deep learning and computer science.
• Communicate results to stakeholders and senior leadership team to guide decisions and product launch.
• Write blogs on our public website showcasing Groove DS & ML work to external audiences.
• Publish research finding in an open-access repository (e.g. ArXiv) and/or in conferences.
• Mentor junior associates and support them in their professional career development.

Requirements:

• 7+ years of experience in a Data / Applied / Research Science or Machine Learning role with a proven track record of developing production-ready algorithms.
• M.S. in Mathematics, Statistics, Computer Science, Engineering, Operations Research, or other quantitative disciplines. Ph.D. preferred. 
• Proficiency in SQL and Python. Experience working in an agile software development environment and with software development life cycle tools preferred.
• End-to-end experience with data exploration process, including querying, cleaning, analysis, and visualization.
• Proficient in developing, testing and validating machine learning / deep learning models.
• Experience in building core product / service features is highly desirable.
• Excellent communication and presentation skills, ability to explain complex ideas / solutions to a non-technical audience.
• Passion for solving technically challenging problems.
• High-energy self-starter with a passion for your work, attention to detail, and a positive attitude.
• Great team player, willingness to collaborate and communicate with others to solve a problem.