Job Description
Collaborate with product design and engineering to develop an understanding of needs
Research and advise innovative statistical models for data analysis
Communicate findings to business stakeholders Enable smarter business processesand implement analytics for actionable insights
Keep current with technology and industry developments
Use various statistical techniques and algorithms to extract knowledge and insights from structured and unstructured data
Establish and mentor junior Data Scientists.
Performing people management responsibility.
Responsible for technology and platforms vision.
Work closely with Data Products Owners for setting up use-cases priorities, Budget and backlog.
Work closely with Technology teams to design, build, test, deploy, maintain and improve technology solutions and models.
Collects and determines data from appropriate sources to assist in determining business needs and requirements.
Interacts with both Data Engineers and business owners for satisfying the use-case requirements
Follows and embraces best practices when it comes to methodologies, standards, and processes.
Spread Design Thinking and Agile methodologies
Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques, and business strategies.
Assess the effectiveness and accuracy of new data sources and data-gathering techniques.
Build tunes and deploy predictive statistical models for extracting business insights.
Exploit ML for developing business use-cases
Provides thought leadership by researching best practices, conducting experiments, and collaborating with business leaders
Requirements
Bachelor's degree in Economics, Computer Science, Engineering, Statistics, Mathematics, Physics, Operations Research, or related discipline with an excellent academic record.
Solid understanding of foundational statistics concepts and ML algorithms: linear/logistic regression, random forest, boosting, GBM, NNs, etc.
Experiences in building data science solutions with real business problems. (e.g. recommendation building, customer journey, customer experience enhancement, etc).
Fluency in at least one of the following languages: Python, Java, Scala, R.
Ability to access, manage, transfer, integrate and analyze complex datasets, especially using SQL and No-SQL.
Experience with sci-kit-learn and pandas (or equivalent tools).
Master or Ph.D. degree (preferred) in computer science, statistics, neuroscience, engineering, mathematics, or physics.
preferred but not must an experience with working on large data sets, especially with Hadoop and Spark.
