Expert Data Scientist

Job Summary

Acts as a technical expert and project leader for the most challenging data science projects. Provides highly technical and analytical assessments of business priorities to senior leadership and drives the implementation of analytic solutions. Acts as a strong influencer and change agent in the organization to advance a databased decision-making culture. Oversees and coaches the team of data scientists to run analytical experiments methodically, evaluate alternative models, and develop predictive models to forecast business performance metrics.

Communicates effectively with technical and non-technical stakeholders with strong domain expertise and business acumen. Leads the research and development of new technologies and best practices within the industry to recommend approaches and strategies that develop the organizations analytical capabilities. Span of Control: 0, Individual Contributor.

• Leads data science projects from end-to-end, collaborating with cross-functional stakeholders, identifying business requirements, gathering data, researching analytics solutions, and integrating solutions into business processes
• Conducts advanced statistical analysis to determine trends and significant data relationships, and proactively recommends areas of improvement
• Develops complex data sets and predictive models to support key decisions to improve safety, employee engagement, operation efficiency, product quality, and customer satisfaction (e.g., cost-benefit, invest-divest, forecasting, predictive, what-if, impact analysis, etc.)
• Prepares and delivers insightful presentations and action recommendations. Educates leaders and crews on complex analytical findings in laymen terms and with storytelling/data visualization
• Identifies and evaluates technologies and provides strategic inputs to advance the organizations analytics capabilities
• Mentors the team of data scientists by guiding their professional development in conjunction with the team manager
• Actively researches new technologies in related subjects and supports the organization to develop data analytics strategies and roadmaps

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

• Bachelors degree and 10 years of experience, inclusive of 3 years of leading experience working as a team or project lead in a data analytical or computer programming function; or
• Masters degree and 8 years of experience, inclusive of 3 years of leading experience working as a team or project lead in a data analytical or computer programming function; or
• Ph.D. degree and 6 years of experience, including 3 years of leading experience working as the team or project lead in a data analytical or computer programming function
• 5 years of experience in qualitative and quantitative analytics (e.g., data mining, regression analysis, hypothesis testing, A/B testing, predictive modeling, model optimization, time series analysis, cluster analysis, natural language processing/text analytics, and segmentation)

Preferred:

• Masters or Ph.D degree with emphasis on coursework of a quantitative nature (e.g., Statistics, Computer Science, Engineering, Mathematics, Physics, Data Science, Econometrics, etc.)
• Advanced business acumen and utility/energy industry experience
• Deep interest and aptitude in data, metrics, analysis, trends, statistics, and program evaluation
• Advanced project management skills
• Experience with publications or conference presentations in a related subject

• Intermediate-level competency 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
• Proven expertise in articulating business questions and pulling data from relational databases (e.g., ORACLE, SQL SERVER)
• Intermediate-to advanced-level programming skills in SQL, Python, R, and in visualization tools such as Power BI, Tableau
• Intermediate- to advanced- level skills in data modeling, data structure, metadata, and the application of complex SQL queries with data from multiple sources, including a Big Data platform (e.g., Azure ADLS and Databricks)
• Experience in designing, building, and supporting a production pipeline for data transformation and validation
• Advanced skills of applied research design, machine learning, prediction, and optimization (e.g., multivariate statistical analysis, unsupervised and supervised learning, predictive modeling, Monte Carlo simulation)
• Exceptional track record of successfully delivering large-scale analytical models and systems that result in substantial positive impact on business operations or customer satisfaction
• Intermediate-level or higher Continuous Improvement knowledge, skills, and certifications
• Self-starter and learning capability in advancing skillset in business processes, data science,…