Manager Marketing

As a Manager of Product Marketing Data & Strategy, your role will involve leading the intersection of data analytics, product marketing, and business decision-making. Your responsibilities will include: - **Data & Advanced Analytics:** - Conducting advanced statistical analysis to understand customer behavior, product adoption patterns, and campaign ROI. - Developing and scaling algorithms to support personalization, lead scoring, and conversion rate optimization. - **Strategic Marketing Insights:** - Partnering with product marketers to shape positioning, messaging, and go-to-market strategies using data-driven insights. - Analyzing competitive landscapes and market trends to support strategic planning. - Delivering high-impact insights and recommendations to cross-functional stakeholders. - **Data Infrastructure & Reporting:** - Defining data requirements and collaborating with engineering and BI teams to ensure clean, scalable, and accessible marketing datasets. - Developing interactive dashboards and self-service tools to democratize marketing performance data across teams. - Owning key performance metrics and attribution models connecting marketing activities to business outcomes. - **Cross-Functional Collaboration:** - Acting as a strategic thought partner to marketing, product, and sales leadership. - Collaborating with go-to-market teams to test hypotheses, run experiments, and iterate on marketing strategies. - Driving alignment on customer definitions, metrics, and business drivers across departments. - **Team & Project Leadership:** - Leading cross-functional analytics initiatives and managing junior data scientists or analysts. - Championing data literacy and insight-driven decision-making across the marketing organization. **Education & Experience:** - Masters degree in data science, Statistics, Economics, Computer Science, Engineering, or related field. - 10+ years of experience in product analytics, data science, strategy roles, preferably in a global consulting environment. - Proficiency in SQL, Python, and data visualization tools (e.g., Tableau, Power BI, Looker). - Experience building models using machine learning libraries and frameworks (e.g., scikit-learn, XGBoost, TensorFlow, etc.). - Strong communication and storytelling skills with the ability to explain complex concepts to non-technical stakeholders. - Proficient with marketing concepts, strategy consulting, and product lifecycle.,