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Lead Revenue Operations Data Scientist

Lead Revenue Operations Data Scientist

Rapid7Boston, MA, United States
1 day ago
Job type
  • Full-time
Job description

Lead Revenue Operations Data Scientist

Rapid7 is looking for an experienced and innovative Data Scientist to join our Revenue Operations team. This is a pivotal role focused on building sophisticated models and leveraging data science to drive smarter business decisions across our Go-to-Customer organization. You'll report to the Director of Revenue Operations Analytics and collaborate with sales, marketing, and customer success leaders to identify and act on opportunities for growth and efficiency.

About the Team

Revenue Operations Analytics is a new, high-impact team focused on leveraging data and advanced analytics to drive growth and efficiency across our Go-to-Customer organization. We serve as a strategic partner to our sales, finance, and customer success teams, providing the insights, models, and tools they need for accurate forecasting, both in-quarter and for strategic long-term planning. Our mission is to transform raw data into actionable intelligence that directly influences our revenue streams and GTM strategy.

About the Role

The ideal candidate is a highly skilled data scientist with a passion for applying advanced analytics to solve complex business problems.

As a Lead Data Scientist, You will be responsible for building predictive models that directly impact our revenue streams and improve the effectiveness of our GTM teams. Specifically, your focus will be on :

  • Account & Opportunity Scoring Models : Build and deploy sophisticated models to predict a customer's propensity to spend, identifying the ideal time to engage with expansion opportunities. You'll also develop opportunity scoring models to help our sales teams prioritize their pipeline and focus on the deals most likely to close.
  • Customer and Renewal Analytics : Develop models to predict renewal risk, allowing our Customer Success teams to proactively engage with at-risk accounts. You will also analyze and segment our customer base to inform strategies for improved retention and engagement.
  • Market and Whitespace Analysis : Utilize advanced analytics to quantify whitespace and total addressable market, providing strategic insights that guide our go-to-market planning and resource allocation.
  • Data Strategy : Partner with our data engineering and business intelligence teams to ensure we have a robust and scalable data infrastructure. You will be a key stakeholder in defining our data strategy, ensuring we capture and leverage the right information to power our models.
  • Stakeholder Communication : Translate complex analytical findings into clear, actionable recommendations for our business leaders. You will communicate insights through presentations, reports, and strategic decisions across dashboards, influencing the company.

The skills and qualities you'll bring include :

  • Experience : A minimum of 6+ years of experience in a data science role, preferably in revenue operations, sales operations, or a related field within a SaaS company.
  • Technical Skills : Deep expertise in statistical modeling, machine learning, and predictive analytics. Familiarity with Random Forest and XGBoost algorithms is preferred. You'll also need strong proficiency in Python or R, and a solid understanding of SQL. Experience with data visualization tools like Tableau or PowerBI is a plus.
  • Problem-Solving : Proven ability to apply data science methods to solve real-world business challenges and drive measurable results. You should be able to work independently to define a problem, build a solution, and communicate the impact.
  • Business Acumen : A strong understanding of the sales lifecycle, go-to-market strategies, and revenue operations. You can connect your models to business outcomes and communicate their value to non-technical stakeholders.
  • Collaboration : Excellent communication and interpersonal skills. You enjoy working in a fast-paced environment and collaborating with cross-functional teams.
  • Core Value Embodiment : Embody our core values to foster a culture of excellence that drives meaningful impact and collective success.
  • We know that the best ideas and solutions come from multi-dimensional teams. That's because these teams reflect a variety of backgrounds and professional experiences. If you are excited about this role and feel your experience can make an impact, please don't be shy - apply today.

    About Rapid7

    At Rapid7, our vision is to create a secure digital world for our customers, our industry, and our communities. We do this by harnessing our collective expertise and passion to challenge what's possible and drive extraordinary impact. We're building a dynamic and collaborative workplace where new ideas are welcome.

    Protecting 11,000+ customers against bad actors and threats means we're continuing to push the envelope - just like we've been doing for the past 20 years. If you're ready to solve some of the toughest challenges in cybersecurity, we're ready to help you take command of your career. Join us.

    #LI-JC1

    Rapid7, Inc. is committed to fair and equitable compensation practices. A candidate's salary is determined by various factors including, but not limited to, relevant work experience, skills, and certifications. We evaluate compensation decisions on a case-by-case basis, and it is not typical for an individual to be hired at the very top of the salary range.

    The salary range for this role in the US is :

    $113,900.00 - 154,100.00 USD Annual

    Salary ranges may vary based on geographical location. This range does not include variable / incentive compensation, equity and benefits (where applicable / eligible).

    All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or any other status protected by applicable national, federal, state or local law.

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    Lead Data Scientist • Boston, MA, United States

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