Head of Data

Whisker•Auburn Hills, MI

30m•Onsite

About The Position

Whisker is redefining what it means to live with cats—designing intelligent systems that remove friction, elevate the everyday, and celebrate the quiet brilliance of feline companionship. Today, Litter-Robot leads the category. Tomorrow, an entire ecosystem that expands what’s possible for cats and the people who love them. We believe the future is feline. And we’re imagining that future today. We work onsite 4+ days a week, with our team based in Auburn Hills, Michigan, and Juneau, Wisconsin. Our team of 700+ passionate pet people thrives on collaboration, innovation, and the occasional office cameo from a four-legged friend. At Whisker, we’re redefining the pet care experience through connected robotics, software, and AI. With products like Litter-Robot® and a growing ecosystem of devices and digital experiences, we are building a category-defining platform at the intersection of hardware, software, and data. As Head of Data, ML & Business Intelligence, you will organize and lead Whisker’s centralized data organization. This role is responsible for unifying a fragmented data environment into a structured, scalable data intelligence center across the company, establishing a single source of truth, and enabling better decision-making and stronger ML/AI implementation across product development, marketing, operations, and the broader business. You will report to the CFO and partner closely with Engineering, Product, Marketing, Finance, and Operations. This is an on-site role. The Head of Data will lead the centralization of data, business intelligence, and machine learning at Whisker, building a cross-functional data organization that supports the full company. This role owns the data lifecycle end-to-end – data creation, organization, visualization, and predictive – and ensures data is reliable, accessible, and actionable across every department.

Requirements

Bachelor’s degree in engineering, computer science, data science, or related field and / or equivalent years of experience
12+ years of experience across data, analytics, BI, or machine learning, including leadership experience
Proven experience building or scaling centralized data organizations
Strong understanding of modern cloud architectures, particularly AWS and Snowflake-based systems, and the ability to partner effectively with engineering teams to integrate product, device, and backend data into a unified data platform
Strong experience in data architecture, data engineering, and business intelligence systems
Experience supporting multiple functions (product, marketing, operations, finance) within a unified data model
Strong understanding of KPI frameworks, dashboarding, and self-service analytics
Experience with machine learning and predictive analytics
Strong leadership, communication, and cross-functional collaboration skills
Maintains confidentiality of proprietary information
Ability to maintain a professional atmosphere in a fast-paced environment with numerous interactions and interruptions
A high degree of initiative, self-motivation, and ability to motivate others
Ability to establish and maintain cooperative working relationships with Team Members and colleagues
Comfortable with office pets (cats, dogs)

Nice To Haves

Experience with IoT, connected devices, or hardware/software ecosystems
Experience with marketing attribution, MMM, and customer analytics
Experience with mobile app analytics and event instrumentation
Experience with operational analytics (supply chain, manufacturing, logistics)
Experience implementing experimentation frameworks (A/B testing)

Responsibilities

Centralize Data Across Whisker
Creates a unified data architecture that integrates product, app, device, marketing, ecommerce, financial, and operational data into a single source of truth.
Defines and owns the full data lifecycle, including ingestion, transformation, storage, governance, quality, and access.
Implements consistent data models, metric definitions, and governance standards to eliminate conflicting reporting across teams.
Builds scalable data pipelines and infrastructure to support both real-time and batch data across Whisker’s ecosystem.
Defines and enforces data governance, security, and privacy standards across the organization, ensuring compliance, proper access controls, and responsible use of customer and operational data.
Build Cross-Functional Data Capability
Establishes a company-wide intake and prioritization model for all data work, including data engineering needs, dashboards, analytics, instrumentation, and ML initiatives. Builds and scales a high-performing team across:
Data Engineering
Business Intelligence
Analytics (Product, Marketing, Operations)
Data Science / ML
Data Management / Governance
Enables self-service analytics through governed datasets, dashboards, and standardized KPI frameworks
Improves efficiency of data teams by separating data engineering, analytics, and BI responsibilities—reducing time spent on data cleanup and increasing time spent on insights
Establishes clear ownership, documentation, and data definitions across all major datasets and business metrics
Partners with Engineering to improve instrumentation across mobile apps, backend systems, and connected devices
Product Development (Hardware, App, Fleet)
Improves product and app instrumentation to enable accurate tracking of feature usage, engagement, and retention
Builds analytics to support product roadmap decisions, including feature adoption, performance, and customer behavior
Partners closely with Engineering to ensure data generated across mobile applications, backend systems, and AWS-based infrastructure is properly instrumented, structured, and accessible for analytics and machine learning
Establishes A/B testing and experimentation frameworks across digital products
Develops visibility into fleet performance, device behavior, and system reliability
Supports future predictive use cases, including device health, fault detection, and behavior modeling
Marketing (Attribution, MTA, MMM, Customer Journey)
Builds internal capability to support multi-touch attribution (MTA) and marketing mix modeling (MMM). Some of this work is already underway and the Head of Data will partner with Whisker’s CMO to fully implement the program
Creates a unified view of the customer journey across acquisition, conversion, retention, and lifecycle
Improves marketing performance measurement, segmentation, and customer-level analytics
Supports budget allocation and channel optimization through clearer ROI visibility
Enables testing frameworks across campaigns, channels, and lifecycle programs
Operations & Finance
Develops dashboards and analytics across supply chain, inventory, logistics, returns, and warranty
Supports demand forecasting, cost optimization, and operational efficiency initiatives
Partners with Finance on revenue reporting, forecasting, CAC, LTV, and margin analysis
Improves visibility into operational performance and key cost drivers
Will support the optimization of our ERP and consideration of a new ERP
Business Intelligence (Company Wide)
Builds and maintains dashboards for all departments and executive leadership
Establishes standardized KPI reporting across Product, Marketing, Finance, WHOps, and CX
Creates a governed semantic layer to ensure consistency across reporting and analysis
Transitions BI from reactive reporting to proactive decision support
Machine Learning & AI
Defines the roadmap for machine learning and AI across product, marketing, and operations, in partnership with our software engineering team, product teams, and beyond.
Builds capabilities for predictive analytics, including LTV, churn, demand forecasting, and personalization.
Partners with Engineering to productionize models and establish MLOps practices.
Ensures ML initiatives are grounded in strong data foundations and aligned to business impact
Performs additional responsibilities when required
Leadership Responsibilities:
Directly supervises department Teams. Carries out supervisory responsibilities following Whisker policies and applicable laws. Responsibilities include interviewing, training, and hiring, planning, assigning and directing work, appraising performance, addressing team issues, and upholding safety and quality guidelines.