Team NetRefer


Unified Competitive Wages. Great Benefits. Positive Work Environment.

Data Number Cruncher

Data and Analytics Team

Positions
1
Location
Malta

Are you good crunching numbers?

 

Can you do 1+ x(x.y)+x3/y^2  = ?

 

Do you like coding?

NetRefer is looking for a data scientist to be part of our Data and Analytics Team, to deliver world class data-driven products information about internal processes of the company.  These products are aimed directly at improving our clients’ bottom-line. Developing such products requires the best brains to discover valuable patterns and insights from the underlying data. The chosen candidate will be a key person in hunting for these insights.

 

Essential Job Functions:

  • The chosen candidate needs to be able to apply statistics, mathematics, machine learning, and predictive modelling to business requirements using various software tools.
  • Discover new information from the underlying data.
  • Ability to extract and compute the data according to business objectives.
  • Ability to visualize the insights through reporting and/or dashboarding.
  • Ability to operationalize Data Science experiments by creating, computing and calling web services.
  • Maintain the current Data Science processes to improve or change them.

 

Skills and Experience Required:

  • Inquisitive skills – to explore data and ask “What if” and “What is” questions.
  • Research for new topics and models with other teams according to business requirements.
  • Proven experience in coding with Statistical or Machine Learning tools
  • Proven experience in data analytics and statistics is a must
  • Proven experience in visualizing data, creating dashboards
  • The ability to query databases.
  • A commercial mind-set with the ability to understand the business strategy.

Essential Skills:

  • Master/PhD in Maths, Statistics or AI field
  • Knowledge of querying the data using SQL
  • Knowledge of R/Python packages

Desired Skills:

  • Knowledge of Financial, Quantitive Analysis
  • Knowledge of the IT architecture of a Data Science work environment.
  • Knowledge of cluster-based approaches for studying data science like Hadoop, HIVE, PIG,  SPARK
  • Knowledge of Dundas or other visualization tools