Data Scientist I

Job Title: Data Scientist I 34801

Description:

• 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.
• Efficiently retrieves internal and external data and ensures that source data is accurate, meaningful and valid for use in analytics and reporting.
• This level combines 2-3 sources of structured data with a consistent identifier. Identifies ways to develop sustainable data provisioning solutions.
• Addresses quality issues for data sets by identifying the root cause and potential solutions.
• Updates or develops dashboards.
• Supports efforts to close data quality gaps by meeting data training needs within the business.
• Works under some supervision.

Responsibilities:

• 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.
• Conduct complex, specialized analyses of reliability data such as Weibull and Competing Failure Mode Analysis, calculating component life and estimating repair costs.
• Locates and acquires data from existing data locations, external sources, and new data sources as needed to support analytics and reporting.
• Organizes and cleans the data to remove quality issues, combines data sources, and provides relevant information which may include developing samples used to create analytics models or reports.
• Creates ad hoc reports and visualizations that support data-driven decisions.
• Works on new data provisioning solutions, explores new ways of organizing data, and focuses on developing sustainable data usage for designated stakeholders including access, costs, and organization processes.
• Participates in creating analytics models by applying data knowledge throughout the modeling process to ensure the data is valid, accurate, and applicable for the intended usage.
• Supports data governance activities by acting as a data steward or custodian of certain data elements.

Education:

• 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)
• Degree in an Information Technology discipline or equivalent experience. - University Degree (4 years or equivalent)
• 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)
• Degree in Engineering discipline or equivalent experience. - University Degree (4 years or equivalent)

Technical Skills & Knowledge:

• 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.
• Specialized skills, knowledge and abilities needed to perform the essential functions of the job.
• Knowledge of statistical analysis, economics and trend forecasting. - Has a good understanding of the principles and can independently use the knowledge.
• Programming skills necessary to create and maintain applications - Has a good understanding of the principles and can independently use the knowledge.
• Understanding of various functions within respective business. - 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.
• Education:
• Formal education or training required to perform the essential functions of the job. Includes degrees, certifications, licenses and/or registration requirements.

Relevant Work Experiences:

• 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, Statistical, SPSS or SAS E Miner - 1 - 3 years
• Previous experience with data modeling tools and managing multiple logical and physical data models.
• Internal or external industry specific experience in relevant discipline.
• Data analytics experience. -
• Industry experience in data mining and hands-on experience in quantitative modeling, analysis and data modeling.