Senior Manager, Data Science - The Knot Worldwide

Job Description
The Knot Worldwide is actively seeking an experienced Senior Data Science Manager to lead our Revenue Data Science team. Our team utilizes advanced analytics and statistical methods to optimize revenue performance, conducting analyses, and correlating vendor health with sales and revenue strategies. As the Senior Manager, your primary focus will be on driving the team's strategic direction, ensuring alignment with broader business objectives. You will lead in constructing machine learning models, delivering reports and analytical tools, designing experiments, and collaborating with cross-functional teams to increase our operational efficiency and drive incremental revenue by supporting Sales, Operations, and Finance stakeholders.

As a Senior Manager of Data Science, you will be responsible for:

• Collaborate with and provide strategic guidance to stakeholders across sales, FP&A, and customer care, ensuring data-driven insights contribute to the overall success of revenue initiatives.
• Lead a team of Data Scientists both strategically and drive the development and the implementation of machine learning models to solve core business problems, such as pricing optimization, elasticity modeling, customer churn, lead scoring, lifetime value, and recommender systems.
• Lead customer segmentation efforts to generate insights that can inform our sales and acquisition strategy in a subscription-based plan scenario.
• Spearhead end-to-end projects, from initial ideation and business alignment to measurement and deployment of insights, ensuring a strategic approach and alignment with broader business objectives.
• Play a pivotal role in assisting teams in defining KPIs, setting strategic goals, and designing and analyzing A/B testing for data-driven decision-making, emphasizing a strategic and impactful contribution.
• Oversee the development and maintenance of reports and data products for the organization, utilizing various tools such as Streamlit, Shiny, Looker, or Qlik sense, to provide actionable insights that contribute to data-informed decisions.
• Effectively communicate, collaborate, and present results to stakeholders within TKWW, driving the adoption of data-informed decision-making processes throughout the organization.
• Explore and implement novel methodologies to analyze data for continuous improvement, staying abreast of industry best practices and emerging trends in data science.
• Mentor and guide team members in analytic and statistical best practices, fostering a collaborative and learning-oriented environment within the Data Science team.

To be successful in this role, you should have:

• Advanced academic background with a master's or Ph.D. degree in Statistics, Mathematics, Data Science, Engineering, or a related field.
• Proven experience in leading and managing data science teams, with at least 3 years of experience in a leadership role.
• Exceptional expertise and demonstrated thought leadership in metrics and models relevant to Retention and Pricing Strategy, emphasizing strategic contributions to organizational goals.
• Mastery of applied statistics, showcasing a deep understanding of hypothesis testing and forecasting with hands-on experience in building ML algorithms to uncover actionable insights on retention and pricing strategy and segmentation.
• Proficiency in advanced SQL and Python programming, with the ability to develop and implement sophisticated data manipulation and analysis techniques.
• A high-level understanding of data architecture, data pipelines, and database design, demonstrating the ability to guide and optimize these processes with Data Platform partners.
• Proficiency in at least one advanced visualization tool, coupled with a strategic approach to data visualization that enhances decision-making processes.
• Excellent communication skills, both written and verbal, with the ability to articulate complex concepts to diverse audiences, including non-technical stakeholders.
• A strategic mindset with the ability to translate complex business problems into innovative analytics opportunities and solutions.
• A collaborative leadership style that fosters a culture of data-driven decision-making across the organization.
• An innovative spirit, constantly exploring and implementing new ideas and approaches to address challenging problems.