Potential candidates should possess a strong analytical mindset and be very comfortable with processing and manipulating large data sets in various formats. 

Hands-on Expertise in Python programming and experience in handling various data science libraries (Pandas, Numpy, Scipy) would be a necessary requirement 

Familiarity with analytics methods (descriptive/predictive/prescriptive) and Business Intelligence tools (Python-Matplotlib, Tableau, QlikSense) would be a definite plus. 

Exposure to Cloud technologies (e.g., Google Cloud), including executing Machine Learning algorithms on Cloud would be definite plus. 
 
Candidates should display interest and initiative in translating a business problem into an analytical problem and determining the appropriate analytical methods to be used. 

Master's Degree or Equivalent

Develop machine learning models and implement ML feature delivery as managed services or on device model. Analyze large and complex data sets to derive valuable insights using BI Tools Collaborate with data engineers to develop data and model pipelines Write production-level code and bring code to production Engage in code reviews Develop and test the machine learning model Design and evaluate approaches for handling large volume of real data streams. Improve existing machine learning models Develop prototype for future exploration. Produce project outcomes and isolate issues Implement machine learning algorithms and libraries Communicate complex processes to business leaders Research and implement best practices to enhance existing machine learning infrastructure