Lead Data Scientist

Job Title: Lead Data Scientist
Total Position: One
Job Type Permanent
Minimum Education: Minimum Masters Degree in Data Science, Computer Science, Business Administration or Statistics. Preferably a Post Doctorate in the relevant field.
Minimum Experience: 6-8+ years experience in data driven field (e.g. BI, DWH, Advance Analytics etc.)
Skills Required:
• Strong problem-solving skills with an emphasis on product development.
• Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
• Experience of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Experience of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
•  Prior experience with visualization tools such as D3.js, HTML, and CSS is a plus.
•  Linux server-side application administration experience (R-Studio Server, R-Studio Connect) a plus.
•  Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, MySQL, etc.
•  Excellent written and verbal communication skills for coordinating across teams.
•  A drive to learn and master new technologies and techniques.
Job Responsibilities:
•  Work closely with our business departments to support their department strategy. Implements this strategy by reviewing our various data sets to understand data trends.
•  Use predictive modelling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
•  Perform strategic data analysis and research to better understand our customers.
•  Ability to draw insights from multiple data sources to provide better visibility into safety/quality related issues.
•  Develop analytical approaches to answer high-level questions and develop insightful recommendations.
•  Develop processes and tools to monitor and analyse model performance and data accuracy.
•  Ability to balance the demands of multiple projects simultaneously.
•  Mentors IT staff and business users regarding data mining and analysis procedures in order to ensure business goals and objectives are met.
•  Assists in preparation and cleansing of data for analysis.
•  Educates business users on advanced analytics best practices.