Job Description:
INNOVATE without boundaries! At Milwaukee Tool we firmly believe that our People and our Culture are the secrets to our success -- so we give you unlimited access to everything you need to provide support to your business unit. Behind our doors you'll be empowered every day to own it, drive it, and do what it takes to support the biggest breakthroughs in the industry. Meanwhile, you'll have the support and resources of the fastest-growing brand in the construction industry to make it happen.
Your Role on Our Team:
As the Director of Data Science & Analytics, you will be the discipline leader for Business Intelligence Engineering, Data Science, and our emerging Forward Deployed Engineering (FDE) capability, and a member of the Data & AI leadership team who co-owns the enterprise analytics and AI strategy alongside VP leadership. Leading a multi-disciplinary organization of BI Engineers, Data Scientists, and FDEs embedded across our agile pods, you will set the vision, standards, and talent strategy for how Milwaukee Tool turns data into decisions and AI into business outcomes across Commercial, Operations, Product, and Corporate functions. Under our Operating Model 2.0, your team members are embedded in cross-functional agile pods; you will own the craft (hiring, developing, and deploying great BI Engineers, Data Scientists, and FDEs) and ensure the work they deliver is high-quality, reusable, and measurably moving the business. This is a full-time leadership role: you will lead builders rather than build yourself, and you will shape how the organization is structured as it scales. Your success will be measured by the business impact of our analytics and AI solutions, the strength of your talent bench, and your ability to scale a high-performing, modern data science and analytics function.
You'll be DISRUPTIVE through these duties and responsibilities:
- Discipline Leadership & Vision: Co-own the enterprise analytics and AI strategy alongside VP leadership, and define and drive the vision, strategy, and multi-year roadmap for Data Science, BI Engineering, and Forward Deployed Engineering, balancing near-term pod delivery with long-term investments in advanced analytics and AI capabilities.
- Operating Model 2.0 & Pod Enablement: Serve as the discipline leader for BI Engineers, Data Scientists, and FDEs embedded across agile pods. Partner with product owners, pod leads, and engineering leaders to staff pods with the right skills, set clear role expectations, and ensure the discipline shows up consistently in every pod.
- Data Science Leadership: Lead and scale the Data Science team by hiring, developing, and retaining top data scientists as the function grows. Set the direction for how machine learning, forecasting, optimization, and advanced analytics are applied across the business, and ensure models move from experimentation into production and deliver measurable value.
- BI Engineering Leadership: Lead and develop the BI Engineering team, building strong career paths and technical depth. Drive the evolution of enterprise reporting, semantic models, and self-service analytics so the business has trusted, consistent, and actionable insights.
- Forward Deployed Engineering: Stand up and scale our FDE capability: full-stack builders who embed with business teams to deliver AI-led solutions end to end, from data to models to GenAI and agentic applications, measured on business impact rather than output.
- Business-Facing Accountability: Own the outcomes of data science and analytics work across Commercial, Operations, Product, and Corporate functions, serving as the primary analytics and data science voice in cross-functional planning, funding discussions, and executive-level communication. Own the function's budget, vendor and contractor strategy, and headcount and investment planning.
- Stakeholder & Relationship Leadership: Build and maintain strong relationships with VP+ business and IT leaders. Partner closely with business-embedded analytics leaders (such as Commercial Analytics) so enterprise and business-side analytics operate as one connected system.
- Cross-Functional Influence: Influence prioritization and funding decisions by clearly articulating the business case for analytics and AI investments and the trade-offs across competing demands. You don't wait to be invited to the table; you earn your seat.
- Talent Strategy & Org Design: Set the talent strategy for the function, including org design, career paths for BIE, DS, and FDE roles, hiring plans, the FTE/contractor mix, and succession planning. Design and build the management layer as the function scales.
- Craft Excellence & Standards: Establish the standards and best practices that make our work trustworthy and reusable, including model development and validation, MLOps, semantic modeling and BI design, code quality, peer review, and shared assets used across pods.
- Platform & Technology Direction: Drive the strategic direction for analytics and AI tooling across our AWS, Azure, and Databricks ecosystems, including ML/MLOps, GenAI, and the BI/semantic layer. Partner with Data Engineering, Architects, and Principals on deep technical decisions while shaping the enterprise Data & AI strategy as a member of its leadership team.
- Responsible AI & Value Realization: Ensure models and AI solutions are governed, explainable, monitored, and adopted. Track and communicate the business value delivered.
- Culture & Team Development: Establish and reinforce a culture of ownership, speed, accountability, and direct communication. Develop senior individual contributors and emerging leaders into future managers and build bench strength intentionally.
- Innovation & Continuous Improvement: Foster a culture of experimentation, encouraging the exploration and adoption of new AI, machine learning, and analytics methods. Drive efficiency through automation, reusable patterns, and modern delivery practices.
The TOOLS you'll bring with you:
- Education: Bachelor's degree in Computer Science, Statistics, Mathematics, Economics, Engineering, or a related quantitative field; Master's degree preferred.
- Leadership Experience: 10+ years of experience in data science, analytics, business intelligence, or related fields, with at least 5 years in a senior leadership role leading leaders (managing multiple teams through managers or senior ICs who lead workstreams) across data science, analytics, and/or engineering, including ownership of budget, headcount, and vendor/contractor relationships.
- Strategic Thinking: Proven ability to set direction for a growing analytics and data science function. You see around corners, anticipate where the business is headed, and position analytics and AI to meet it.
- Discipline Leadership: Proven ability to lead a craft (setting standards, career paths, and the quality bar) for practitioners embedded in cross-functional or product teams.
- Data Science & AI Fluency: Strong working knowledge of machine learning, statistical modeling, forecasting, optimization, experimentation, and GenAI/LLM solutions, with the depth to challenge approaches, assess talent, and guide technical direction through Principals and senior individual contributors.
- Analytics & BI Fluency: Strong understanding of enterprise BI, semantic modeling, data visualization, and self-service analytics at scale.
- Stakeholder & Relationship Leadership: Deep experience building trust and influence with VP+ business leaders, IT executives, and cross-functional partners.
- Talent Development & Org Building: Experience hiring, growing, and retaining strong data science and analytics talent, and scaling a function through rapid growth, including building a management layer.
- Business Acumen: You translate business problems in commercial, operations, product, and corporate contexts into analytics and AI solutions, quantify their value, and speak the language of both sides.
- Cultural Alignment: A mindset that aligns with our company culture of ownership, speed and agility, and candid communication.
Other TOOLS we prefer you to have:
- Forward Deployed & Embedded Delivery: Experience building or leading forward-deployed, embedded, or solutions engineering teams that deliver directly alongside business users.
- Agile & Product Operating Models: Experience leading a discipline within a pod-based or product operating model.
- Cloud Data & AI Ecosystems: Experience with AWS, Azure, and Databricks, including their machine learning and GenAI services.
- MLOps & Responsible AI: Experience putting models into production at scale with monitoring, governance, and responsible AI practices.
- Industry Domain Experience: Experience in manufacturing, industrial, or consumer products, for example pricing, demand forecasting, supply chain, or connected products.
- Global/Multi-Entity Organizations: Experience with global or multi-entity organizations, including cross-region collaboration.
- Change Management & AI Adoption: Experience driving adoption of analytics and AI solutions and leading organizational change.
- Matrixed Environment Leadership: Experience operating in a matrixed environment where influence matters more than authority.
Working Conditions:
The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
- Frequently required to stand, walk, bend, stretch, reach, and effectively communicate with others in the workplace
- Sitting for prolonged periods of time
- Prolonged exposure to computer screens
- Repetitive use of hands and fingers to operate office equipment, machinery, hand tools and/or power tools
- Specific vision abilities required by this job include close vision, color vision, peripheral vision, depth perception, and ability to adjust focus
- May require to wear personal protective equipment which includes, but is not limited to, safety glasses, gloves, and hearing protection
- May work in laboratories and/or controlled, enclosed, restricted areas
- Noise levels range from moderate to loud
- Must be able to lift up to 50 pounds at a time
- May require travel dependent on company needs
We provide these great perks and benefits:
- Robust health, dental and vision insurance plans
- Generous 401 (K) savings plan
- Education assistance
- On-site wellness, fitness center, food, and coffee service
- And many more, check out our benefits site HERE (https://www.milwaukeetool.jobs/Benefits).
Milwaukee Electric Tool Corporation is an equal opportunity and affirmative action employer seeking to employ and advance in employment qualified persons without discrimination and to not allow harassment of any employee or applicant because of race, ethnicity, color, religion, sex, sexual orientation, gender identity, genetic characteristics, physical or mental disability, national origin, age, status as a protected veteran, and any other status protected by local, state, or federal law.
Milwaukee Tool is an equal opportunity employer.