Decision Science Analyst

Reece Group

1d•$67,000 - $92,125

About The Position

The Decision Science Analyst will architect the analytical foundation of Red Robin's Growth, Intelligence & Decisioning capability. Equal parts data miner, performance analyst, model builder, and strategic thought partner, this role will build the analytical frameworks, measurement methodologies, and decision support infrastructure leadership relies on to understand performance and optimize business outcomes. This role will provide ongoing support and performance visibility across Marketing, Loyalty, CRM, Paid Media, Culinary, Pricing, Customer Experience, and First Choice initiatives and will be responsible for connecting customer, transaction, menu, pricing, media, digital, and operational data to drive enterprise decision making. The Decision Science Analyst will help build analytical capabilities for Red Robin, leveraging data from customer platforms, engagement platforms, digital commerce platforms, enterprise data environments, customer experience platforms, and intelligence platforms to create actionable insights and recommendations. This position will both build something new while supporting critical initiatives such as First Choice segmentation, pricing strategy, menu innovation, customer growth, loyalty optimization, media effectiveness, and hyper local marketing approaches. Success requires a builder mindset and comfort operating in an environment where analytical frameworks, measurement standards, and decision support capabilities are actively being developed. The role will partner closely with internal stakeholders including Marketing, Culinary, Pricing, Finance, Customer Experience, Operations, and Executive Leadership, while also collaborating with external partners including Analytica, Surface, media agencies, and strategic analytical partners supporting growth initiatives and customer decisioning.

Requirements

3 to 5 years of experience in analytics, decision science, customer analytics, business intelligence, marketing analytics, commercial analytics, or performance analysis.
Strong SQL skills and demonstrated ability to extract, manipulate, and analyze large datasets from multiple sources.
Experience building dashboards and analytical solutions using Power BI, Tableau, Looker, or similar business intelligence platforms.
Proven ability to analyze and communicate business performance drivers including ROI, ROAS, customer value, retention, frequency, incrementality, segmentation, and campaign effectiveness.
Experience translating complex analytical findings into actionable business recommendations.
Strong problem-solving skills and ability to work independently in ambiguous environments.
Ability to manage multiple projects and priorities while delivering high quality analytical outputs.
Effective communication skills with the ability to present findings to both technical and non-technical stakeholders.
Demonstrated curiosity, intellectual rigor, and desire to connect data to business outcomes.
Builder mindset with the ability to create new processes, frameworks, models, and capabilities from the ground up.

Nice To Haves

Experience in restaurant, hospitality, retail, ecommerce, loyalty, subscription, or multi-unit consumer businesses.
Experience working with customer transaction intelligence platforms, customer analytics platforms, or customer data platforms.
Familiarity with customer engagement platforms, loyalty platforms, customer experience platforms, and digital commerce ecosystems.
Experience supporting pricing, menu, culinary, promotional, customer, loyalty, media, or customer experience analytics.
Experience with customer segmentation, predictive modeling, forecasting, customer lifetime value, retention modeling, or advanced analytical methodologies.
Experience working with enterprise data warehouses, cloud data environments, lakehouses, or modern analytics ecosystems.
Familiarity with location intelligence, trade area analytics, customer migration analysis, and hyper local growth strategies.
Experience supporting test and learn programs, incrementality measurement, experimental design, or optimization frameworks.
Experience leveraging customer transaction data to generate insights related to acquisition, retention, frequency, menu affinity, and customer growth.
Exposure to statistical analysis, Python, R, machine learning, or advanced analytical techniques.

Responsibilities

Conduct hands on analysis of campaign, loyalty, CRM, menu, pricing, customer, media, and business performance.
Quantify ROI, ROAS, incrementality, visit lift, retention impact, customer value, profitability, and channel effectiveness.
Develop analytical methodologies used to evaluate performance across marketing, pricing, loyalty, customer experience, culinary, and growth initiatives.
Partner with Finance and business leaders to identify drivers of traffic, sales, frequency, profitability, and customer growth.
Lead test and control design, incrementality measurement, forecasting, and performance analysis.
Evaluate promotional effectiveness and business impact across value, menu, loyalty, and customer acquisition initiatives.
Support enterprise planning through analytical assessments of opportunities, risks, and growth drivers.
Develop decision frameworks that improve the speed and quality of business decision making.
Support media performance analysis, attribution, and investment optimization across paid and owned channels.
Build measurement frameworks supporting First Choice, customer segmentation, pricing strategy, and guest acquisition initiatives.
Mine and connect data across customer, loyalty, transaction, menu, pricing, operational, digital, and media ecosystems.
Extract and analyze data from enterprise data warehouses, lakehouses, customer data environments, and transactional platforms.
Develop customer segmentation, behavioral clustering, predictive modeling, and opportunity identification frameworks.
Support First Choice segmentation and hyper local marketing strategies through customer, geographic, behavioral, and trade area analysis.
Leverage location intelligence and spatial analytics tools to identify market opportunities and competitive advantages.
Build scalable datasets, analytical frameworks, and reusable decision support tools.
Analyze customer lifetime value, retention, engagement, frequency, migration, and loyalty performance.
Develop analytical solutions supporting menu optimization, pricing strategy, customer acquisition, customer retention, and media effectiveness.
Support development of future analytical capabilities enabled through Bikky and other customer intelligence platforms.
Translate disparate data sources into integrated views of customer and business performance.
Serve as an analytical partner to Marketing, Loyalty, CRM, Paid Media, Culinary, Pricing, Customer Experience, and Growth teams.
Identify opportunities to improve customer acquisition, engagement, retention, frequency, and profitability.
Support menu innovation and pricing decisions through customer and transaction analysis.
Develop analytical recommendations that influence strategic and operational business decisions.
Translate complex analytical findings into clear business recommendations.
Partner with stakeholders to prioritize opportunities and quantify business impact.
Support annual planning, quarterly business reviews, and ongoing performance optimization efforts.
Provide analytical support for enterprise growth initiatives and emerging business opportunities.
Build analytical dashboards supporting Marketing, Loyalty, CRM, Pricing, Culinary, Customer Experience, and First Choice initiatives.
Create measurement dashboards focused on customer behavior, loyalty performance, pricing, menu performance, media effectiveness, and growth opportunities.
Develop self-service analytical environments that allow stakeholders to explore performance drivers and business opportunities.
Build reporting solutions that improve visibility into customer, menu, pricing, and marketing performance.
Maintain analytical datasets and reporting structures that support recurring business reviews and decision making.
Ensure analytical outputs are scalable, repeatable, and aligned to enterprise reporting standards.