Director Data Science And Analytics at The Knot Worldwide

ABOUT THE ROLE AND OUR TEAM
TKWW is looking for a Director of Data Science & Analytics to build statistical models, reports, and analytical tools that will increase our operational efficiency and drive incremental revenue. A key focus of this role will be on monetization and pricing of our marketplace, but the role also encompasses supporting a variety of business stakeholders, including Sales, Operations, Finance, and certain product lines internationally and in the US. This is a highly technical position where data science, statistics, and machine learning play a major role, but knowledge of analytics and data engineering are also required. The Director will report to the Head of Data and will be responsible for growing and setting the strategy and vision for their team.
 
RESPONSIBILITIES

Manage, grow, and mentor a global team of data scientists and analysts.
Inform our pricing strategy and develop algorithmic methods to optimize product pricing across different countries, markets, and categories.
Build statistical and machine learning models to solve core business problems, such as pricing optimization, elasticity modeling, customer churn, lead scoring, lifetime value, and recommender systems.
Build a reporting stack tailored to the stakeholder needs, including high-level executive reports and domain-specific operational reports.
Lead vendor segmentation efforts to generate insights that can inform our sales and acquisition strategy.
Improve upon existing methodologies for measuring marketplace performance in a subscription-based plan scenario.
Explore and experiment with alternative auction-based monetization plans, including pay-per-lead and pay-per-booking approaches.
Think holistically about the data needs of the organization across data science & analytics, business intelligence, machine learning, and data engineering.
Design and conduct A/B testing experiments and advocate for an iterative learning culture.
Develop tools and data products that automate manual work, increase operational efficiency, and empower users via self-service.

 
SUCCESSFUL CANDIDATES HAVE

Experience with implementing pricing optimization and elasticity models with demonstrable business impact.
Advanced degree in statistics, data science, operations research, engineering, or computer science (PhD highly desired).
Excellent communicator with ability to translate technical concepts to non-technical audiences.
Strong SQL and Python programming skills.
Strong knowledge of applied statistics and machine learning.
Experience working at a two-sided marketplace or eCommerce company.
High-level understanding of data architecture, data pipelines, and database design.
Knowledge of visualization and proficiency in at least one visualization tool.
4 years of data science leadership.
Strong track record of influencing the organization and driving tangible business impact.

                                                                                                                                                                                                                                                        
 
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