Remote Kigo - Director, Data Science & Analytics Products na Augeo Affinity Marketing

Kigo is a technology company paving a new path forward for loyalty and digital advertising. Kigo’s innovative platform connects advertisers with high-value customers through some of the world’s most popular loyalty and rewards programs. As a subsidiary of Augeo, a leading global loyalty platform and services company, we leverage decades of industry expertise supporting Fortune 500 brands and their users across the globe. Kigo’s expanding loyalty network enables 40,000+ local and national brands to reach millions of customers with proven engagement, spending power, and brand affinities—creating new revenue streams for loyalty programs while delivering more engaging, rewarding experiences. Join Kigo and step into the future of loyalty and digital advertising! Here, your work will have an impact, driving meaningful results and shaping the loyalty experience of tomorrow. 

Summary

We're seeking a Director of Business Intelligence & Data Products to lead Kigo's data science and analytics organization while building innovative data products that position Kigo as the leading global AI-driven loyalty platform. This is a unique hybrid role that combines product management, data science, engineering, and advanced analytics to drive business outcomes through intelligent data solutions.  

We're looking for a self-starter with strong entrepreneurial instincts combined with a consistent drive to execute with urgency and excellence. Reporting directly to the President and Chief Product Officer, you'll be hands-on building machine learning models, conducting advanced statistical analysis, and developing data products that optimize customer experiences and business outcomes. You'll also manage contractor relationships and vendor partnerships to extend capabilities in data science, data engineering, and ML/AI engineering.  

This role is for a technical leader who can balance strategic vision with hands-on execution across the full data science lifecycle while building organizational capability through a combination of internal talent and strategic contractor relationships. If you want to build cutting-edge data products while establishing a world-class data organization in a fast-growth environment, this is your opportunity. 

Key Responsibilities

Strategic Leadership & Technical Execution 

• Define and execute organizational data strategy in partnership with the CPO and CTO while personally contributing to advanced statistical analysis, predictive modeling, and machine learning initiatives 
• Build and develop internal data science capabilities while establishing strategic contractor relationships and vendor partnerships in data science, data engineering, and ML/AI engineering 
• Establish data science methodologies, experimentation frameworks, and model governance practices while planning for strategic organizational growth 

Data Science & Product Development 

• Lead development of predictive models for customer behavior, churn prediction, lifetime value estimation, and personalization algorithms using advanced statistical techniques and machine learning 
• Conduct deep-dive statistical analysis to uncover insights from large datasets, perform hypothesis testing, and drive data-driven decision making across the organization 
• Design and build data products that combine statistical modeling, machine learning, and real-time optimization to deliver measurable business value to customers and partners 

Advanced Analytics & Insights Discovery 

• Perform complex statistical analysis and modeling to identify patterns, trends, and opportunities in customer behavior, platform performance, and market dynamics 
• Develop and implement A/B testing frameworks, causal inference methodologies, and experimentation strategies to measure and optimize product performance 
• Lead insights discovery initiatives that transform raw data into actionable business intelligence through advanced analytical techniques and data mining 

Technical Architecture & Engineering 

• Oversee the design and implementation of enterprise-scale data science infrastructure on AWS, including model deployment, monitoring, and real-time scoring systems 
• Manage contractor relationships and vendor partnerships to extend capabilities in specialized areas including data engineering, ML operations, and advanced analytics 
• Lead evaluation and implementation of advanced analytics tools, ML platforms, and statistical software within the AWS ecosystem while ensuring effective integration with contractor-delivered solutions 

Business Partnership & Revenue Impact 

• Partner with Product, Sales, and Strategic Partnerships to embed predictive models and statistical insights into core business processes and customer-facing features 
• Develop customer-facing analytics products that leverage machine learning and statistical modeling to drive platform adoption, engagement, and revenue growth 
• Support enterprise customer implementations with sophisticated predictive analytics, custom modeling, and advanced insights capabilities 

What Sets You Up for Success

Technical Leadership & Data Science Expertise 

• 10+ years of combined experience in data science, machine learning, and statistical analysis with 3+ years in leadership roles building data capabilities through a combination of internal talent and contractor relationships 
• Deep expertise in statistical modeling, machine learning algorithms, predictive analytics, and experimental design with hands-on experience in Python/R, SQL, and advanced statistical packages (scikit-learn, TensorFlow, PyTorch, etc.) 
• Strong background in data science and ML services (Databricks, Snowflake, Google BigQuery, Google Vertex AI, SageMaker, EMR, Redshift, Lambda) with experience managing contractor relationships and vendor partnerships for specialized data science and engineering capabilities 

Product & Business Acumen 

• 5+ years of experience in e-commerce, digital advertising, or loyalty platforms with proven track record of building data products that drive revenue growth and customer success 
• Experience with product management principles, user research, and translating business requirements into technical solutions through statistical analysis and modeling 
• Strong understanding of A/B testing, causal inference, customer analytics, and business metrics with ability to design and execute complex experiments 

Communication & Strategic Thinking 

• Exceptional ability to communicate complex statistical concepts and model results to technical and non-technical stakeholders including C-level executives and external customers 
• Strong entrepreneurial mindset with self-starter mentality and proven ability to execute with urgency and excellence in fast-paced, ambiguous environments 
• Experience managing contractor relationships, vendor partnerships, and cross-functional collaboration to deliver complex data science projects with distributed teams 

Preferred Qualifications 

• Degree in data science, statistics, computer science, economics, or related quantitative field with experience in loyalty/rewards platforms, financial services, or customer analytics 
• Experience with customer data platforms (CDPs), marketing automation, and personalization systems with track record of thought leadership through industry speaking, publications, or open-source contributions 
• Background in causal inference, econometrics, or behavioral analytics with experience in international or multi-market statistical analysis 

Benefits 

• Comprehensive benefits package including health, dental, and vision 
• 401(k) with company match 
• Executive development and continuous learning opportunities 
• Remote-friendly work environment with occasional travel to St. Paul, MN 
• Collaborative and innovative team culture with direct access to executive leadership 
• Opportunity to define the future of loyalty and digital advertising through data science innovation 

St. Paul, MN or Seattle, WA preferred, but open to remote 

Kigo is an equal opportunity employer committed to diversity and inclusion in the workplace.