Data Scientist 1

MAJOR PURPOSE:

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.

MAJOR DUTIES:

Description of the major duties performed in this job.

• 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.

QUALIFICATIONS:

Competencies, technical skills, formal education and relevant work experience critical for successful

individual performance of essential functions.

Technical Skills & Knowledge:

Specialized skills, knowledge and abilities needed to perform the essential functions of the job.

• Business process knowledge of assigned area(s) and/or function(s). - Has a good understanding of the

principles and can independently use the knowledge.

• Knowledge of advanced data gathering and analysis techniques, including statistical analysis. - Has a

good understanding of the principles and can independently use the knowledge.

• Knowledge of appropriate industry - Has a good understanding of the principles and can independently

use the knowledge.

• Good interpersonal, negotiation and conflict resolution skills. - Yes

• Excellence in verbal and written communication forms with emphasis on persuasive communication,

tact and negotiation. - Has a good understanding of the principles and can independently use the

knowledge.

• Quantitative analytical skills - Has a good understanding of the principles and can independently use

the knowledge.

Education:

Formal education or training required to perform the essential functions of the job. Includes degrees,

certifications, licenses and/or registration requirements.

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

• Degree in an Economics discipline or equivalent experience. - University Degree (4 years or equivalent)

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

Relevant Work Experiences:

Type and amount of experience necessary to perform the essential functions of the job. May include specific

roles and/or an understanding of a particular function, organization, industry or product line.

• 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

Position Title: Data Scientist

Remote role or onsite if local. Will need to train onsite about 2 weeks but will be 1 week first and then return for another week.

Data collection (ex. SQL data query, Power Automate)

Data transformation

Data analysis

Business Intelligence Application skills; Power BI required, others encouraged

Enterprise Data Lake (EDL) experience preferred

Ability to communicate with both technical and process experts and non-expert stakeholders

Familiar with Accounting or Business Administration concepts and terms