Data Scientist

Collaborates with business and analytics leaders to generate insights and answer business questions by using analytics techniques such as advanced data visualization, statistical analysis, randomized testing, predictive modeling, forecasting, optimization, and/or machine learning. Proposes innovative ways to look at problems by using these approaches on available enterprise data as well as customer third party data and information. Validates findings using experimental and iterative approaches.

This level performs basic statistical analysis of low to moderately complex data from a single source, with heavy reliance on industry/standardized tools and existing models. Output is reviewed by higher-level Data Scientists or Analytics Manager for execution.

• Works with data sets and performs appropriate analytical methodology to provide insights and decision modeling for the business.
• Creates and implements algorithms which manage the data to enable it to be analyzed in an efficient manner.
• Supports the communication of derived insights, especially through appropriate visualization techniques.
• Supports the identification of the required data sources and works with Data Wranglers and/or IT to implement methodologies to retrieve and use this data.
• Stays abreast of the latest appropriate analytical techniques and recommends these where needed. Explains implementation and usage in business terms.
• Applies analytical techniques to prospect for business insights and find patterns in data which could be valuable for the business.

• Quantitative analytical skills
• Knowledge of appropriate industry
• Good interpersonal, negotiation and conflict resolution skills.
• Excellence in verbal and written communication forms with emphasis on persuasive communication, tact and negotiation.
• Business process knowledge of assigned area(s) and/or function(s).
• Knowledge of advanced data gathering and analysis techniques, including statistical analysis.

Education:

• Degree in a Math discipline or equivalent experience. University Degree (4 years or equivalent)
• Economics University Degree (4 years or equivalent)
• Statistics University Degree (4 years or equivalent)

Work Experience:

• Internal or external industry specific experience in relevant discipline. (1 - 3 years)
• Data analytics experience. (1 - 3 years)
• Background or proven experience in mining data for analytics insights. (1 - 3 years)
• Good exposure to enterprise statistical tools like SAS, Statistica, SPSS or SAS E Miner (1 - 3 years)

• Maintaining cost forecast - Working with buyers to ensure accurate forecast
• Developing & distributing monthly cost metric reports for the team
• Completing cost analysis in support of negotiations with suppliers

• Good interpersonal, negotiation and conflict resolution skills
• High level of attention to detail and accuracy
• Experience analyzing large amounts of data
• Bachelor’s degree (Business degree is preferred but not required)

• Experience with JDSN (MyProjects)
• Experience with Tableau or Power BI;
  Databricks