Manager, Data Analytics (Meter to Cash)

Posting End Date:  

Work Place Flexibility: Hybrid 

Legal Entity: Entergy Services, LLC 

Job Summary/Purpose

Internally classified as “Mgr, Operations Reporting/Analytics, the data analytics manager is one of the critical leadership roles in the Meter to Cash organization. The data analytics manager is responsible and accountable for leading a team of data analysts, data scientists, and data engineers who will design, develop, implement and manage informatics and analytic solutions to help business functions identify and remediate customer pain points in the Meter to Cash process. The data analytics manager is the overall lead for developing, testing, implementing, and potentially maintaining entire analytics solutions composed of statistical modelling implementations plus visualization layers, modelling types may include machine learning, linear/logistic regression, neural net, decision trees, etc. The manager communicates insights to a variety of audiences from machine-learning experts to business analysts and interacting with customers of all levels to review expected outputs, applicability to business challenges, and model measurement. The data analytics manager is always seeking out new tools, concepts and methods to improve and incubate analytics models and stay current with external market leading trends and methods. The data analytics manager’s primary responsibility is to lead and develop a team of data analysts, data engineers, and data scientists. The data analytics manager will develop standards and processes to which the data analytics team will follow. The data analytics manager will develop and continually improve analytics work processes and collaborate with other managers to develop and improve processes. The data analytics manager will develop and maintain productive, collaborative working relationships with the business leadership team.

 

Job Duties/Responsibilities

1. Manage high performing, responsive team of data analysts, data scientists, and data engineers that are able to not only keep up with but also pioneer and innovate in analytics.
2. Work with large, complex data sets to solve difficult, non-routine analysis problems, applying advanced analytical methods as needed.
3. Translate business questions and concerns into specific analytical questions that can be answered with available data using statistical methods.
4. Focus on entire analytics solutions, keeping business adoption and usability in mind. The solutions might be composed of a visualization layer built in Power BI or Java and/or customized advanced analytical models in SAS, python, Rand/ or ML.
5. Leverage a broad stack of technologies — Python, R, ML, SAS, Spark, and more to reveal the insights hidden within huge volumes of numeric and textual data.
6. Apply Statistical and Machine Learning methods to specific business problems and data.
7. Ensure data quality throughout all stages - ingestion, processing, normalization, and transformation.
8. Develop comprehensive knowledge of business domain data structures and metrics, advocating for changes where needed for product development.
9. Work with engineers to develop efficient data querying and modeling framework.
10. Partner with Enterprise Data Engineering to ensure the data accuracy and consistency.
11. Collaborate with business to prioritize and execute on high impact use cases.
12. Constantly seeking out high-end, market-leading analytics concepts, solutions and tools to grow our analytics capabilities. Continually research and evaluate emerging technologies to stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.
13. Communicate proposals and results in a clear manner backed by data and coupled with actionable conclusions to drive business decisions.
14. Establish, monitor, report, and continually improve work processes to which the data analytics team will adhere.

 

Minimum Requirements

Minimum education & experience required of the position

• Bachelor’s degree and 8+ years of experience working in a data science, algorithmic engineering, or machine learning capacity, ideally in energy industry, or in lieu of degree, 12+ years’ experience.
• 5+ years of experience in managing and mentoring data science, data engineering, and analytics teams.
• Master’s Degree in quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent) preferred

 

Minimum knowledge, skills and abilities required of the position

• Experience with statistical software (e.g. R, Python, MATLAB) and database languages (e.g. SQL)
• Experience building data science models (Regression, Decision Trees, K-Means, etc.)
• Experience