Director, Data Science

The Director, Data Science is responsible for helping set the vision for improving Bloomin Brands Customer Relationship Management (CRM) efforts through effective use of guest data.

The Director, Data Science will be a key business partner to the VP Digital and Sr. Director of Loyalty Strategy and CRM. By improving our access, understanding, and analysis of our customer data, we will be able to drive more informed decision-making and guest-focused strategies.

The Director, Data Science will lead the efforts to leverage data-related tools and develop analytic processes to provide a competitive advantage by effectively understanding, segmenting, and targeting our valued customers. This role is based in our Tampa Restaurant Support Center and will work a hybrid schedule (three days per week onsite).

ESSENTIAL DUTIES

• Partner with Digital IT Team and CRM team to ensure customer data integrity and usefulness: Identify opportunities and develop strategies to acquire, integrate, manage, and optimize new and disparate data sources to enrich existing customer data set.
• Ensure appropriate quality control in place to maintain data accuracy and integrity.
• Build and maintain robust data management processes.
• Design and automate processes in Microsoft Azure and/or Alteryx to facilitate the manipulation and analysis of customer data.
• Streamline linkage of data sources - notably enriched customer data.
• Develop and implement customer analytics data processes.
• Utilize POS data to develop targets for marketing programs.
• Determine differentiators of key customer segments.
• Identify opportunities within the data to drive growth by identifying customer needs and preferences.
• Design, implement, and deploy machine learning models for various business applications.
• Collaborate with cross-functional teams to integrate machine learning models into existing systems.
• Optimize models to ensure accuracy is within bounds, improve model performance and fine-tuning.
• Monitor and alert relevant teams to key metrics and KPIs.
• Collaborate with cross-functional teams to leverage data science methodologies in developing personalized customer communication strategies, ensuring alignment with customer preferences, and enhancing overall engagement and satisfaction levels.
• Expand the scope and influence of the analytics function through strategic business decisions, influencing skills, and effective communication.
• Improve organizational effectiveness by leveraging cross functional partnerships, shared accountability, analytical thinking, drive for results, and attention to detail.

REQUIREMENTS

Education:

• Bachelors degree in information technology, Statistics, Analytics, Math, Computer Science, Engineering, or similar discipline required.
• Masters Degree preferred.
• Certification in data science or analytics (e.g., Certified Analytics Professional, SnowPro Certified Advanced Data Scientist) preferred.

Experience/Skills:

• 7+ years of experience with data management and quantitative analytics
• Experience working with customer level data - preferably restaurant, retail, or hospitality loyalty programs.
• Experience defining customer metrics and methods (e.g. R/F/M, Customer Lifetime Value, Churn Analysis)
• Expertise in clustering/segmentation for use in Loyalty and email campaigns
• Strong technical skills with direct experience in a Microsoft Azure environment.
• Familiarity with Alteryx and data visualization tools such as Power BI is preferred.
• Working knowledge of programming languages such as R, Python, SQL; deep familiarity
• Experience/familiarity with advanced programming concepts, Machine Learning methods (ARIMA, XGBoost, etc.), AI algorithms, deep learning libraries (TensorFlow, PyTorch, etc.), and big data technologies (Spark, Hadoop, etc.).
• Ability to manage other technical talent directly or indirectly through partnership and/or vendor management.
• Proven ability to work closely and effectively with multiple levels of an organization and experience in communicating with and influencing a non-technical audience.
• Proven ability to manage and integrate data, tools, processes, and systems across disparate data sets.
• Demonstrated expertise of data management, process development, modeling, and analytics.
• Ability to develop, implement, and communicate complex statistical models.
• Stays on top of emerging trends in data science methods, technologies, and systems.