Data Scientist (PMO Process Integration)

Job Summary

Responsible for translating business requirements into analytical constructs and using data to propose solutions for effective decision making.

Collects, validates, transforms, and cleanses data, as well as performs quantitative analysis to derive insights. Runs analytical experiments in a methodical manner and regularly evaluates alternative models and techniques.

Develops predictive models to forecast business performance metrics and provides recommendations for strategic decisions.

Responsible for teaching others the tools, techniques and best practices in self-service reporting, data analysis and predictive analytics.

Key Accountabilities

Performs in-depth analyses (e.g., cost-benefit, invest-divest, forecasting, predictive, what-if, impact analysis, etc.

to help the company focus on key decisions to improve safety, employee engagement, operational efficiency, product quality, and customer satisfaction

• Develops, modifies, and automates reports, builds and prototypes dashboards to provide insights, and provides analytical solutions
• Responsible for discovering insights from Big Data to help shape or meet specific business needs and goals.
• Develops and maintains analytical models through understanding data, evaluating technologies, optimizing algorithms, experimenting and validating models
• Delivers effective presentations that tell compelling stories about analytical insights
• Performs data cleansing and blending processes to produce analytic data sets for use by a variety of downstream purposes
• Implements new statistical, mathematical, machine learning or other methodologies for modeling or analysis
• Utilizes business knowledge to translate goals into data-based deliverables, such as predictive models, pattern detection analysis or optimization algorithms
• Trains and enables self-service reporting capability and use of Business Intelligence tools for supported business unit(s)
• Conducts research to identify relevant data for developing prototypes and proof-of-concepts
• Collaborates with cross-functional stakeholders to understand business needs, formulate complete end-to-end analyses that includes business requirements, data gathering, analysis, scaleable solutions, and presentations

Minimum Education & Experience Requirements

This is a dual-track base requirement job; education and experience requirements can be satisfied through one of the following two options :

• Bachelors degree with emphasis on coursework of a quantitative nature (e.g., Statistics, Computer Science, Engineering, Mathematics, Physics, Data Science, Industrial / Organizational Psychology and Econometrics, etc.
• and 3 years of experience working in a data analytical or computer programming function;
• Masters degree with emphasis on coursework of a quantitative nature (e.g., Statistics, Computer Science, Engineering, Mathematics, Physics, Data Science, Industrial / Organizational Psychology and Econometrics, etc.

and 1 year of experience working in a data analytical or computer programming function

Other Qualifications

Preferred :

• Masters or PhD degree in Data Science
• Experience in quantitative analytics (e.g. data mining, regression analysis, hypothesis testing, predictive modeling techniques, and model optimization)
• Knowledge and intermediate-level skills in data modeling, data structure, and the application of complex SQL queries with data from multiple sources, including Big Data platform (e.

g., Hadoop, AWS, Azure)

• Familiarity with Cloud environments
• Experience with SAP Business Intelligence tools and SAP CRM, ISU, and BW data
• Familiarity with Continuous Improvement concepts and applications (e.g., six sigma, lan)
• Strong written and verbal communication skills
• Utility / energy or customer-oriented industry experience

Other Requirements :

• Intermediate-level experience with data mining and statistical analysis using analytical packages / tools (e.g., R, SAS, SPSS, Stata, MATLAB, Minitab, etc.)
• Intermediate-level experience in articulating business questions, pulling data from relational databases (e.g., SAP BW, ORACLE, SQL SERVER) and using advanced excel and statistical tools (e.

g., Minitab, Alteryx, Advanced Excel with VBA, R, Python, SAS, SPSS, Stata, MATLAB, etc.) to conduct in-depth analysis to support decision making

• Intermediate-level proficiency in business intelligence tools (e.g., Microsoft PowerBI, Tableau, SAP, Business Objects (BOBJ), etc.)
• Intermediate-level programming skills in SQL, C / C++ / C#, PHP, Java, Python, R, ASP, or SAS
• Understanding of applied research design and machine learning (e.g. multivariate statistical analysis, unsupervised and supervised learning, predictive modeling)
• Self-starter and quick learner; advances self and others' knowledge and skill sets in business processes, data science, new analytical frameworks, technologies, and applications
• Interpersonal, analytical and problem-solving skills, including ability to communicate technical information and complex data analytics to a non-technical audience
7 days ago