This job has responsibility for proposing and developing new forecasting models, building accounts receivable health modeling infrastructure, designing and prototyping business and financial metrics, overseeing department operational and financial metric reporting, providing analytical support to Customer Financial Operations functions, and supporting business initiatives. Design and prototype new collections, credit, bad debt, operational risk metrics, and assist with the establishment of contr... more detailsols and monitoring activities. Building the account receivable modeling infrastructure including the production models, automated reports, databases, job scheduling systems. Provide quantitative analyses for Revenue Management functions, including collections and the credit groups. Work closely with all Customer Financial Operations functions, business owners, and IT on developing efficient reporting tools. Maintain and expand the existing reporting system, analytical tools, and databases which are used for measuring and analyzing revenue risks associated with the company's business practices. Participate in the SAS system architecture design and enhancements. Diligently pursue information and conduct research to understand accounts receivable risk modeling and risk mitigation techniques, introduce best business practices, and propose new modeling methodologies to support best practices. Providing analytical support for Management by addressing difficult problems with quantitative methods and providing manageable and useful solutions. PRIMARY DUTIES AND ACCOUNTABILITIES Leverage in-depth technical knowledge of predictive analytics, statistics, modelling techniques and simulation approaches to develop valuation, risk management, and pricing models. (15%) Conduct research and produce proof-of-concept demonstration systems to test new quantitative modeling approaches and solutions to complex problems. (15%) Translate quantitative and business concepts into efficient, robust, supportable system design and architecture. (15%) Provide leadership, training, and mentorship to less experienced technical analysts on the team and in the organization. (15%) Partner with IT to develop complex data structures and a business intelligence platform for reporting end user data mining. (10%) Partner with stakeholder analytics teams across the enterprise to expand the use and gather feedback on the models and systems. (10%) Leverage quantitative modeling and simulation techniques (e.g., System Dynamics approach) to produce robust scenario analysis, in support of utility strategic planning and assess the impact of emerging technologies and other potential business disrupters to utility business model. (10%) Provide input into the development of evaluation plans and critically review evaluation reports; contribute to broad discussions relating to policy issues for planning and evaluation; work effectively with independent evaluation contractors. (10%) JOB SCOPE Reports to the Manager within the Energy Acquisition group Works under minimal supervision, relying on knowledge, skills and judgment acquired through education and relevant experience to plan and accomplish assigned tasks and goals
MINIMUM QUALIFICATIONS
Bachelor's degree in quantitative field (e.g., Statistics, Applied Mathematics, Economics, Engineering). Minimum 4-7 years relevant experience Thorough understanding of applied and financial mathematics concepts and techniques (including advanced statistical techniques) Ability to use a broad range of development languages (e.g. C/ C , Python, Perl, Matlab, etc. e.g., SAS, SQL, Vensim, R, Python, STATA, Excel, etc.), and databases query languages Ability to quickly master industry fundamental concepts including energy commodity markets, portfolio valuation, and system dynamics Should be self-driven and able to work in (and lead) team sizes ranging from individual contribution to several members. Demonstrate proficiency in accessing database and extracting intelligence from large complex datasets to support business initiatives. Demonstrate the ability to work independently and provide mentorship to less experienced team members Excellent communication skills and close collaboration with internal and external stakeholders are required. Ability to translate data analysis and findings into coherent conclusions and actionable recommendations. Masters or Phd Energy industry experience Prior experience in an operation research role In-depth experience in one or more programing language. Background in applied system dynamics theory Ideal candidate with have experience performing advanced quantitative analysis and developing and/or validating risk models to support senior managers in running their quantitative strategies. Knowledge about econometric methods, probability theory and statistics. Knowledge about System Dynamics theory is preferred for the Energy Analytics position.
PREFERRED QUALIFICATIONS
Masters or PhD in quantitative field Energy industry experience In-depth experience in one or more programing language. Background in applied system dynamics theory Experience performing advanced quantitative analysis and developing and/or validating models to support senior managers in running their quantitative strategies. Knowledge about System Dynamics theory.
