Combining business acumen with state-of-the-art technology in Data Mining (statistical modeling, computer programming, large database and system) to provide business intelligence, decision and production support to Segment Marketing, Strategic Planning, Finance, Risk Control and Regulatory on marketing the RIGHT product with the right price to the RIGHT people through the RIGHT channel and on the RIGHT time with WELL procured supply.
Conduct Campaign Development, Marketing and Portfolio analysis:
Work together with marketing team to develop marketing learning agenda. Design and execute testing cells and implement the learning plan.
Use EPNPV (Expected Prospects Net Present Value) or LTV (Life Time Value) models to segment potential marketing population to target the profitable segments through different marketing channels.
Score and append targeting flags to prospect/customer lists for campaign file cut.
Post campaign analysis on enrollment, conversion rate, customer usage, customer credit, COA (cost of acquisition), gross margin, marketing return and NPV (net present value) by channel and product.
Analyze the testing cell result and develop the learning regarding effectiveness of different pricing, message, incentive, # of mailing and channel strategy.
Apply advanced statistical technique to develop targeting models to predict enrollment, usage, length of tenure, and default. Constantly track the models performance and update the models.
Profile and compare particular segments, such as Hispanic customer, Balance billing, OAM (online account management), on demographic, usage, payment behavior, product preference, and attrition/switch behavior and etc.
Develop and update statistic model to predict attrition/switch models and customer value calculation engine. Calculate customer LTV score for call center retention efforts.
In depth analyze the attrition/switch drivers and quantify their impacts.
Develop & Operate Portfolio Acceptance and Attrition Report:
Monthly/Quarterly customer count reports for accounting book closing. They include customer count by business segment, territory, product and campaign at begin and end of period, new start and new stop for both current and historical period.
Monthly/Weekly AA (acceptance and attrition) book. It reports detailed acceptance, attrition and transfer service activities by type, segment, product and timing for both current and historical period. It also reports switchers destination.
Ad Hoc reports for marketing, finance, planning, supply, risk and regulatory departments.
Advanced Degree (Master or Ph.D) in Quantitative Fields Required, such as Economics, Engineering, Mathematics, Statistics or related fields
1-2 years in statistical modeling, quantitative analysis and Modeling with experience of a large scale data. 1 year in the gas or power industry with knowledge of the retail electricity market preferred.
Statistical Modeling Skill:
Have solid statistical modeling education and training plus practical modeling experience in a large data scale environment. Be proficient in statistical test procedure, liner regression, and logistic regression.
SAS & Other programming and computer Skill:
Proficient in SAS SQL, BASE, STAT programming. Comfortable with SAS MACRO.
Good at Microsoft Office.
Additional Knowledge, Skills and Abilities:
Ability to translate complex business issues into achievable analytical learning objectives and actionable analytic projects.
Solid understanding of the use and interpretation of graduate level multivariate statistical techniques and sampling methods, such as multi-variants regression, ANOVA, factor analysis, cluster analysis, and main components analysis.
Ability to interpret complex analytic results and develop practical business implications.
Understanding of utility business, to include service process, market structure/pricing and competitive environment.
Strong written and oral communication skills.
Keen attention to detail.
Ability to work as a team member in a fast paced environment.
To apply for this job, please send your resume to firstname.lastname@example.org