Manager - Customer Analytics

Role: Manager, Customer AnalyticsStatus: Regular, Full TimeReports to: Senior Manager, Marketing Analytics Department: MarketingDivision: Enercare Home and Commercial ServicesLocation: Hybrid - Markham Compensation: $74,817 - $118,211 Please note that the compensation range listed includes base salary and potential incentive pay. Incentives such as bonuses are not guaranteed and depend on individual performance and company results. Actual compensation within the range will be determined based on skills, experience, and qualifications.The Manager, Marketing Analytics works collaboratively with the Customer Base Management team , Acquisition team and Product team to deliver analysis and insights to advance data-based decision making within Enercare’s Home Services Division. They will collaborate with the Marketing team on projects to measure, assess performance and make recommendations on digital campaign, offer, product and asset performance.The individual will work through all phases of analytic requests from identifying requirements to assembling key information to applying statistical and analytic techniques to interpreting findings to preparing and presenting findings. They will work closely with business partners across the business including the Data Strategy and Operations Team and Information technology team. This position is supported by the Senior Manager, Marketing Analytics.Your analysis and recommendations will have a direct and immediate impact on the company’s success. This role will also be involved in projects to support customer and product growth/attrition goals. Your campaign analysis will be critical to support the direction of our future marketing initiatives.This is a great opportunity for a data-driven, forward-thinking analytic professional looking to join a growing organization positioned to be the premier provider of essential home, commercial services and energy solutions in North AmericaKey Responsibilities: Design and implement processes to support data-based decision making through the planning, in-market and post assessment phases of Marketing initiatives and campaigns Develop and deploy predictive models to support core business outcomes by using machine learning and advanced analytics techniques, including propensity modeling, churn prediction, and customer lifetime value prediction, etc. Support model deployment, monitoring, governance, and lifecycle management in production environments. Assist with customer segmentation, forecasting, classification, and optimization projects. Produce comprehensive in-campaign and post-campaign reports on campaign performance, highlighting key findings, insights, and recommendations for optimization. Communicate results in a concise and effective manner to ensure that key business partners understand key levers to drive business performance. Deliver KPI performance data for weekly and monthly reviews, reporting on KPIs such as open rates, CTR, leads, conversion rates, website traffic, calls volume, web forms and social media engagement. Work closely with agencies to integrate information from multiple digital data sources. Qualifications: Minimum 5 years’ experience in delivering analytics and data science results in a data-driven organization. Undergraduate or Graduate degree in a quantitative discipline Advanced proficiency in Python and SQL, with demonstrated experience developing production-grade analytical solutions. Working experience building, validating, and deploying machine learning models using libraries such as Scikit-Learn, XGBoost, LightGBM, CatBoost, TensorFlow, or similar frameworks. Experience working with cloud-based analytics platforms such as Microsoft Fabric Familiarity with MLOps principles, including model lifecycle management, monitoring, version control, experimentation, and deployment practices. Strong business acumen, with an excellent understanding of marketing, sales fundamentals. Proven track record of developing analytic presentations to drive action for business units. Demonstrated ability to collaborate with diverse cross-functional teams to achieve results.