VP, B2B Marketing Data Science

News Corporation•New York, NY

32d•$225,000 - $275,000•Hybrid

About The Position

Reporting to the Senior Vice President of Marketing Data Science & Technology, this role will spearhead the development of marketing data science strategies for our B2B lines of businesses and products. This seasoned data science professional will establish these capabilities from the ground up for the B2B area. They will lead the development and implementation of foundational data-driven marketing & sales strategies in the B2B businesses, leveraging data science and AI.

Requirements

15+ years experience in marketing data science, with a strong focus on B2B
Degree in a quantitative field such as Data Science, Statistics, Mathematics, or related disciplines.
Expertise in data-driven decision-making, with hands-on experience in leveraging data to optimize marketing performance
Hands-on expertise in advanced analytics, data mining, forecasting, and predictive analytics.
Proficiency in programming languages such as Python, R, or SQL.
Strong business acumen and the ability to effectively communicate complex concepts to non-technical stakeholders.

Nice To Haves

Experience in the media industry is good to have.
Experience using media mix models and data visualization tools like Tableau.

Responsibilities

Data-driven Marketing Strategies: Utilize advanced analytics techniques to analyze large volumes of customer data, including industry information, transactional data and competitive insights. Derive actionable insights to execute strategies that drive customer growth and revenue across channels and across the buying lifecycle.
Marketing Measurement & Attribution : Measuring impact of marketing and sales activities. Multi-touch attribution to understand which channels and touchpoints drive conversions
Segmentation and Targeting: Identifying high value prospects by analyzing firmographics, behavior and transaction history
Lead Generation & Optimization: Development of ML models to assign lead scores based on past conversions and engagement patterns and help identify new leads. Develop whitespace analysis and build cross-sell and upsell models.
Forecasting and Budgeting : Collaborate closely with marketing and finance teams to monitor performance against budgets. Develop multiple sensitivity scenarios to aid senior leadership in strategic planning
Churn Prediction & Retention : Identify clients with high churn risk and help improve retention. Build lifetime value models for pricing and risk management.
Dashboards: Build a suite of relevant dashboards to monitor key performance indicators and insights.
Stakeholder Collaboration: Work closely with cross-functional teams, including marketing, sales, product, and finance, to understand their business needs and translate them into data-driven solutions. Present insights and recommendations to senior executives and stakeholders in a clear and compelling manner.