Senior Director, Decision Analytics

Description

Sprout Social is seeking a Senior Director, Decision Analytics to join our Strategy & Business Operations team. In this senior leadership role, you will head our centralized Decision Analytics function, overseeing the data science and analytics teams that power strategic choices across the entire company.

This isn't a passive reporting role. You are tasked with reinventing how Sprout approaches data—moving beyond retrospective reporting to build a predictive, insights-driven culture where data actively shapes business outcomes. Inheriting a team mid-transformation, you will define how every major function at Sprout utilizes data to accelerate growth and maximize business impact for years to come.

Why Join Sprout's Strategy & Business Operations Team?

As a pillar of the Strategy & Business Operations organization, you will sit at the critical intersection of business strategy and technical data infrastructure. We are completely rebuilding our centralized data approach, making this role the single most important hire for our department's future.

What we offer: The opportunity to manage real ambiguity with true ownership, backed by direct visibility to the Chief Product Officer and Sprout's executive leadership.

We are a team that values curiosity, a fierce bias toward action, and leaders who can move fluidly between high-level strategy and granular execution. If you want to leave a lasting legacy on a scaling company's data culture, this is where you belong.

What you'll do

Own and lead Decision Analytics, Sprout's centralized analytics and data science function, spanning domain-specialized pods supporting Marketing, Revenue, Product, and Finance across the full organization

Set the vision, standards, and operating model for how Decision Analytics works at Sprout, including how the team prioritizes, partners with stakeholders, and measures its own impact

Drive a fundamental shift in how Sprout's business teams use data: from reactive reporting to proactive, insight-driven decision-making that creates measurable business impact

Serve as the primary analytics and data science thought partner to senior business stakeholders across the organization, building deep relationships, understanding what each team is trying to accomplish, and guiding the team to deliver the highest-leverage work

Connect the dots across the organization, understanding what individual pods are working on, what business stakeholders need, and what is the best use of the team's time and capability

Be a hands-on leader: willing to get into the weeds alongside your team when needed, help work through a complex analysis or model, unblock a problem, or bring the right people into the room

Lead and develop a team of managers, analysts, and data scientists across multiple domain pods, creating a culture of proactive partnership, intellectual curiosity, and high standards

Partner closely with the Director of Data Enablement on data infrastructure and analytics engineering requirements, ensuring the analytical layer is built on a trustworthy and scalable data foundation

Champion AI-forward thinking across the analytics and data science function, identifying opportunities to incorporate AI and automation into how the team works and what it delivers

Drive change management as the organization completes its transition to a centralized analytics model, building trust with stakeholders, establishing new ways of working, and helping the team thrive in a new operating structure

Collaborate cross-functionally without ego; this role requires a genuine collaborator who is more invested in outcomes than ownership

What you'll bring

You are a seasoned data leader who pairs technical and analytical depth with sharp business fluency. You are just as comfortable diving into a complex modeling problem with a data scientist as you are advising a CRO on pipeline strategy. A natural collaborator, you excel at translating sophisticated data science into clear, actionable business strategies, and you thrive when transforming ambiguous challenges into structured, high-impact solutions.

Minimum Qualifications

Experience: 12+ years in analytics, data science, or a related field, including 5+ years leading teams within a SaaS or subscription-based business.

People Management: 5+ years experience of hiring, developing, and mentoring a high-performing team of managers, analysts, and data scientists.

Leadership: Proven success scaling and managing a centralized or hybrid analytics function that simultaneously supports diverse cross-functional business units.

SaaS Fluency: Deep, fluent understanding of core SaaS metrics across the customer lifecycle (e.g., ARR growth/composition, NRR, GRR, pipeline velocity, CAC payback, LTV:CAC, and product activation).

Strategic Altitude: The ability to move fluidly between high-level executive strategy and granular, hands-on technical execution.

Preferred Qualifications

Change Management: Experience leading an analytics organization through a major consolidation, restructure, or operating model transformation.

Technical Depth: Hands-on familiarity with the modern data stack (SQL, Python, dbt, cloud warehouses, BI/visualization tools like Tableau/Hex/Looker) and a foundational understanding of ML modeling frameworks and experimentation design.

Capability Building: Experience expanding advanced data science capabilities alongside core analytics, including predictive modeling and ML-based forecasting.

AI Innovation: An AI-forward mindset with practical experience integrating AI tools and automation to accelerate and scale analytical workflows.

How you'll grow

Within 1 month, you'll plant your roots, including:

Build relationships with your direct reports, key business stakeholders, and cross-functional partners across Data Enablement, Product Operations, and Strategy & Business Operations

Develop a deep understanding of Sprout's business model, the domains your team supports, and the current state of the analytics and data science function you're inheriting

Assess the team's current ways of working, backlog, and stakeholder relationships — and identify the highest-leverage opportunities to build trust and early momentum

Within 3 months, you'll start hitting your stride by:

Establishing a clear operating model for how Decision Analytics works — how work gets prioritized, how pods partner with stakeholders, and how the team communicates its impact

Building credibility as a strategic analytics and data science partner with senior stakeholders across the organization

Identifying gaps in tooling, process, or capability and developing a clear point of view on how to address them

Within 6 months, you'll be making a clear impact through:

Owning the full Decision Analytics function with confidence — managing pod leads, guiding prioritization across domains, and serving as the primary escalation path for the business

Demonstrating a measurable shift in how business stakeholders experience the analytics function: more proactive, more strategic, more trusted

Beginning to shape the longer-term vision for how Decision Analytics evolves as Sprout's data maturity and analytical ambition grow

Within 12 months, you'll make this role your own by:

Leading Decision Analytics through its next phase — from a newly consolidated function to a mature, high-performing team with a clear identity and a strong reputation across Sprout

Establishing a team culture defined by curiosity, proactive partnership, and a relentless focus on business impact — not just analytical output

Positioning Decision Analytics as an indispensable driver of how Sprout makes decisions, allocates resources, and pursues growth

Of course what is outlined above is the ideal timeline, but things may shift based on business needs and other projects and tasks could be added at the discretion of your manager.