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Director, Decision Science

Sustain.Life

Sustain.Life

United States · Denver, CO, USA · Charleston, SC, USA · Missoula, MT, USA · Bozeman, MT, USA · Ames, IA, USA · New York, NY, USA · Remote
USD 177k-284k / year + Equity
Posted on Jan 3, 2026

We are seeking a strategic, technically strong Director of Decision Science to lead our Data Science and Business Intelligence teams. In this role, you will set the vision, guide a high-performing team, and drive Data Science and BI initiatives that influence decisions across the business. You will partner with cross-functional leaders to solve high-impact problems, elevate our self-serve BI capabilities, and embed data science into core business operations. This role reports to the VP of Data & Analytics.

What You'll Do

  • Vision and Strategy Leadership: Define and own the multi-year Data Science and BI strategy and roadmap, ensuring direct alignment with enterprise priorities and quantifiable business outcomes (e.g., revenue growth, operational efficiency)

  • Team Leadership & Development: Recruit, mentor, and manage a high-performing, multi-disciplinary team of Data Scientists, BI Analysts, and BI Engineers, establishing a culture of innovation, operational excellence, and continuous professional development

  • Strategic Business Partnership: Act as the primary analytic partner to business unit leaders (Sales, Product, CS, Marketing, etc.) to define and deliver high-impact, decision-support data products, including predictive models and AI-powered self-service insights

  • Analytical Translation: Translate complex, ambiguous business challenges into structured analytical strategies, guiding teams to deliver high-quality, decision-ready solutions

  • Agile Delivery & Model Lifecycle: Drive an agile, iterative delivery process and oversee end-to-end predictive model lifecycle management, from ideation and validation through scalable deployment, monitoring, and optimization

  • Executive Communication & Storytelling: Communicate clear, actionable, and data-driven recommendations to all audiences, including senior and executive leadership, shaping strategy through compelling, tailored narratives

  • Data Platform Collaboration: Collaborate closely with Data Engineering and Analytics Engineering to design and scale enterprise data assets, features, and metrics that meet evolving analytical needs

  • Governance & Responsible AI: Establish and enforce best practices for metrics design, experimentation, and data governance. Champion data ethics, compliance, and responsible AI standards to promote transparency and trust

  • Enterprise Data Strategy: Partner with leaders across Data Platform, Data Product Management, and Data Governance to develop and execute the overarching Enterprise Data Strategy

What You’ll Need

Minimum Qualifications

  • 8+ years of experience in Data Science, Machine Learning, or related analytical fields, including 3+ years leading high-performing technical teams

  • Advanced degree (MS/PhD) in a quantitative discipline (e.g., Computer Science, Statistics, Mathematics, Operations Research, or similar)

  • Demonstrated ability to translate ambiguous business problems into analytical frameworks and deliver measurable business impact

  • Experience in SaaS or B2B environments, especially where data products directly enable go-to-market, customer success, or product strategy

  • Hands-on experience deploying and operating ML models in production, including monitoring, optimization, and lifecycle management

Preferred Qualifications

  • Deep expertise in statistical modeling, causal inference, experimentation design, and applied analytics to drive business decisions

  • Strong familiarity with modern data ecosystems, including cloud data warehouses (Snowflake, BigQuery), data modeling best practices, orchestration tools, enterprise BI platforms (e.g., Looker, Tableau, Sigma), and MLOps/ML lifecycle platforms

  • Experience building or applying NLP, recommendation engines, forecasting models, or other advanced analytical solutions

  • Strong programming skills in Python and proficiency with modern ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch)

  • Demonstrated ability to design, govern, and scale standardized metrics, dashboards, and self-service BI workflows across business functions

  • Exceptional communication and stakeholder-management skills, with the ability to influence senior leaders and simplify complex concepts for diverse audiences

  • Proven success in hiring, developing, and scaling technical talent across Data Science and BI disciplines

Working Conditions & Travel Requirements

  • Ability to travel to meet with customers and/or key stakeholders, product teams in other Workiva locations (up to 25%)

  • Reliable internet access for any period of time working remotely, not in a Workiva office

How You’ll Be Rewarded

✅ Salary range in the US: $177,000.00 - $284,000.00

✅ A discretionary bonus typically paid annually

✅ Restricted Stock Units granted at time of hire

✅ 401(k) match and comprehensive employee benefits package

The salary range represents the low and high end of the salary range for this job in the US. Minimums and maximums may vary based on location. The actual salary offer will carefully consider a wide range of factors, including your skills, qualifications, experience and other relevant factors.

Employment decisions are made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other protected characteristic.

Workiva is committed to working with and providing reasonable accommodations to applicants with disabilities. To request assistance with the application process, please email talentacquisition@workiva.com.

Workiva employees are required to undergo comprehensive security and privacy training tailored to their roles, ensuring adherence to company policies and regulatory standards.

Workiva supports employees in working where they work best - either from an office or remotely from any location within their country of employment.

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