Description:
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.
What You’ll Do:
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.
Essential Duties and Responsibilities:
This list of duties and responsibilities is not all-inclusive and may be expanded to include other duties and responsibilities as deemed necessary.
Centralize Data Across Whisker
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Creates a unified data architecture that integrates product, app, device, marketing, ecommerce, financial, and operational data into a single source of truth.
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Defines and owns the full data lifecycle, including ingestion, transformation, storage, governance, quality, and access.
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Implements consistent data models, metric definitions, and governance standards to eliminate conflicting reporting across teams.
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Builds scalable data pipelines and infrastructure to support both real-time and batch data across Whisker’s ecosystem.
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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
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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
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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
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Establishes clear ownership, documentation, and data definitions across all major datasets and business metrics
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Partners with Engineering to improve instrumentation across mobile apps, backend systems, and connected devices
Product Development (Hardware, App, Fleet)
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Improves product and app instrumentation to enable accurate tracking of feature usage, engagement, and retention
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Builds analytics to support product roadmap decisions, including feature adoption, performance, and customer behavior
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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
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Establishes A/B testing and experimentation frameworks across digital products
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Develops visibility into fleet performance, device behavior, and system reliability
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Supports future predictive use cases, including device health, fault detection, and behavior modeling
Marketing (Attribution, MTA, MMM, Customer Journey)
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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
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Creates a unified view of the customer journey across acquisition, conversion, retention, and lifecycle
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Improves marketing performance measurement, segmentation, and customer-level analytics
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Supports budget allocation and channel optimization through clearer ROI visibility
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Enables testing frameworks across campaigns, channels, and lifecycle programs
Operations & Finance
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Develops dashboards and analytics across supply chain, inventory, logistics, returns, and warranty
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Supports demand forecasting, cost optimization, and operational efficiency initiatives
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Partners with Finance on revenue reporting, forecasting, CAC, LTV, and margin analysis
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Improves visibility into operational performance and key cost drivers
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Will support the optimization of our ERP and consideration of a new ERP
Business Intelligence (Company Wide)
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Builds and maintains dashboards for all departments and executive leadership
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Establishes standardized KPI reporting across Product, Marketing, Finance, WHOps, and CX
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Creates a governed semantic layer to ensure consistency across reporting and analysis
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Transitions BI from reactive reporting to proactive decision support
Machine Learning & AI
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Defines the roadmap for machine learning and AI across product, marketing, and operations, in partnership with our software engineering team, product teams, and beyond.
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Builds capabilities for predictive analytics, including LTV, churn, demand forecasting, and personalization.
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Partners with Engineering to productionize models and establish MLOps practices.
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Ensures ML initiatives are grounded in strong data foundations and aligned to business impact
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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.
Requirements:
What You’ll Bring:
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Bachelor’s degree in engineering, computer science, data science, or related field and / or equivalent years of experience
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12+ years of experience across data, analytics, BI, or machine learning, including leadership experience
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Proven experience building or scaling centralized data organizations
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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
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Strong experience in data architecture, data engineering, and business intelligence systems
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Experience supporting multiple functions (product, marketing, operations, finance) within a unified data model
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Strong understanding of KPI frameworks, dashboarding, and self-service analytics
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Experience with machine learning and predictive analytics
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Strong leadership, communication, and cross-functional collaboration skills
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Maintains confidentiality of proprietary information
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Ability to maintain a professional atmosphere in a fast-paced environment with numerous interactions and interruptions
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A high degree of initiative, self-motivation, and ability to motivate others
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Ability to establish and maintain cooperative working relationships with Team Members and colleagues
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Comfortable with office pets (cats, dogs)
Not Required but Nice to Have!
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Experience with IoT, connected devices, or hardware/software ecosystems
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Experience with marketing attribution, MMM, and customer analytics
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Experience with mobile app analytics and event instrumentation
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Experience with operational analytics (supply chain, manufacturing, logistics)
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Experience implementing experimentation frameworks (A/B testing)
Benefits & Purrks:
Join a tenacious, inventive company that empowers team members to chart their own path, lead by grounding decisions in the “why”, and has a strong sense of empathy and openness to new perspectives. Be a part of exciting growth, work with incredible people, and create tomorrow’s pet products—plus a whole lot of extras. You will also be provided with:
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Premium Medical/Dental/Vision insurance
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Paid parental leave
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Whisker Parents Program
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1 day "pawternity" leave for new pet adoption
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Pet Insurance Discount
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401K match
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Flexible spending accounts
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Company-paid short-term disability and life insurance
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Employee Assistance Program (EAP)
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Generous paid time off
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14 Paid Holidays
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Top of the line equipment
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Pet-friendly office
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Whisker products and swag
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Continuing education Support
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On-site gym with Peloton
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Referral program
Statement of Inclusivity:
We believe different perspectives make Whisker better and strive to create a place where everyone has equal opportunities to thrive.
Please ensure to regularly check your email spam folder for any communication from Whisker to avoid missing important updates regarding your application status.
Whisker will not ask you to interview with an AI chat bot. We ask that all interviewees refrain from using any AI tools during interviews with Whisker team members.
