Who are we?

UpGuard’s mission is to make life easier for security teams. We meticulously create robust solutions that enable our customers to identify, assess, and remediate cybersecurity risk across their attack surface, vendor ecosystem, workforce, and trust relationships. Our integrated cyber risk posture management platform combines comprehensive security ratings, instant risk assessments, templated security questionnaires, threat intelligence capabilities, and agentic AI to give organizations a holistic view of their risk surface.

Our Analytics team at UpGuard supports all of our teams to extract key insights from the data that we collect. We extract data from multiple sources and build insightful dashboards to display key metrics and support leaders to make decisions. We also build integrations between systems to seamlessly collect required data.

Why are we hiring for this role?

As UpGuard continues to scale at an increasing rate, our Marketing and Sales funnel becomes more and more critical to our growth. As a result, we are looking for someone to not only maintain our funnel’s measurement mechanisms, but obsess over movements, declines and improvements in our conversion rates and volume. We are looking for someone to provide leadership, prediction and reliability to help our Growth and Demand functions make the right decisions and foresee changes in our economic environment.

We are looking for someone with 5+ years of experience working with Analytics, Marketing Operations or Revenue Operations roles, with a measurement, analytics and insights component to their remit. We work as lean teams at UpGuard so we’re looking for someone self-sufficient that’s able to work cross functionally with the Marketing, Revenue, Product and Operations teams to achieve their goals.

What you'll do?

Be a decision-maker, not a service desk: Sit at the table with Marketing, Sales, and Product to shape go-to-market bets for net-new logos. Bring a clear point of view, recommend the next best action, and drive follow-through (owners, timelines, expected impact).
Apply metric-tree thinking with a common currency: Tie input levers (traffic quality, lead velocity, meeting rate, stage conversion, win rate, ACV) to a shared north star for new business (e.g., new-logo ARR or new-logo pipeline $), so trade-offs and priorities are explicit.
Own the net-new pipeline health loop: Define clear targets and early-warning signals across the funnel (Lead -> MQL -> SQL -> Opportunity -> Closed-Won), monitor pipeline coverage vs. goals, and flag slippage and bottlenecks before they impact quarterly new-logo targets
Analyse and and work with the Data Engineering team to connect systems end-to-end: Stitch together Google Ads, HubSpot/Salesforce, Segment/product analytics, and attribution data to identify the channels, messages, and ICP segments that most efficiently create sales-accepted opportunities and closed-won new customers.
Operationalise analytics for speed: Close logging/definition gaps, simplify company-accepted metric definitions, and automate weekly GTM readouts so go-to-market teams can self-serve and leave each review with clear next actions.
Run high leverage deep dives: Size the upside of new-logo initiatives, quantify trade-offs (CAC payback vs. channel mix), and use outlier/edge-case analyses (e.g., SLA misses on inbound demos) to drive cross-functional fixes that unstick the funnel.
Forecast and predict outcomes: Build pragmatic forecasting loops for net-new logos (stage-weighted pipeline, show rate, meeting-to-opportunity, and win-rate trends) and introduce predictive risk signals that help leadership adjust plans early.

What you'll bring?

Exceptional communication and data storytelling skills: You can translate complex data into compelling narratives and actionable insights for stakeholders in Marketing, Sales, and Leadership.
Deep commercial acumen: A strong understanding of how a B2B SaaS funnel operates and the ability to connect marketing activities directly to revenue outcomes like pipeline and new logo ARR.
A structured, hypothesis-driven approach to problem-solving: You excel at moving from broad, ambiguous questions to specific, testable analyses that yield clear recommendations.
Hands-on experience with a modern GTM tech stack: Proven ability to work with data from systems like Salesforce, HubSpot, Google Analytics, and Segment to create a unified view of the customer journey.

What will give you an edge

Experience building predictive models: You've built and deployed models for lead scoring, churn prediction, or pipeline forecasting.
Advanced knowledge of marketing attribution: Deep understanding of various attribution models (e.g., multi-touch, data-driven) and experience implementing or refining them to guide investment.
Experience in a high-growth B2B SaaS or cybersecurity company: You understand the unique pace, metrics, and challenges of our specific industry.
Familiarity with data warehousing and BI tools: You have worked with platforms like BigQuery, Snowflake, or Redshift and have experience building dashboards in tools like Looker, Tableau, or Mode.
A history of presenting findings directly to senior leadership: You are comfortable and confident in delivering strategic recommendations to VPs or C-level executives to influence decision-making.