Lead Data Science Analyst, GTM Strategic Analytics and Insights

United States Digital Space LLC; Denver (CO); On-site; USD 1 - 2; Full time

Job summary

Klaviyos is seeking a Lead Data Science Analyst to join the GTM Strategic Analytics & Insights team. You will serve as a senior individual contributor, building AI-first predictive models, conducting deep-dive analyses, and partnering with GTM leadership to improve pre- and post-sales outcomes.

You will own forecasting and decision systems, develop customer intelligence models, and communicate complex analyses to senior stakeholders in a fast-moving SaaS environment.

Qualifications

• 6+ years of professional experience in an advanced analytics or data science role; SaaS experience strongly preferred.
• Deep expertise in statistical inference and modeling, including supervised techniques (regression, classification, gradient boosting, decision trees) and unsupervised techniques (clustering, PCA, anomaly detection, topic modeling).
• Hands-on experience designing and deploying AI/LLM-based solutions, including prompt engineering, fine-tuning, RAG pipelines, or LLM-integrated analytics workflows; you approach new problems with an AI-first mindset.
• Familiarity and experience with distributed coding projects, including using Git for code management.
• Advanced proficiency in Python (pandas, numpy, scikit-learn, xgboost, statsmodels, and LLM/AI libraries such as LangChain, OpenAI SDK, or HuggingFace) and SQL; working knowledge of DBT
• Own and scale end-to-end data pipelines, including orchestration with Airflow and transformation/modeling with dbt; design reliable, testable, and modular workflows that support production-grade analytics and machine learning use cases, with a focus on performance, data quality, and maintainability.
• Develop and iterate on time-series forecasting frameworks using approaches such as ARIMA/SARIMAX, ETS, MSTL, and machine learning-based models; evaluate performance through rigorous backtesting and continuously improve model accuracy and business applicability
• Experience building data visualizations and dashboards across platforms such as Tableau, ThoughtSpot, matplotlib, seaborn, plotly, or similar tooling.
• Strong project ownership: experienced operating to a roadmap, managing milestones and deliverables, and delivering high-quality work product in a timely manner
• Comfortable with autonomy and ambiguity, with a proactive orientation toward identifying and solving problems before they're fully defined
• Excellent written and verbal communication skills, including experience preparing materials for executive audiences

Responsibilities

• Build and maintain advanced predictive and time-series models across use cases such as demand forecasting, capacity planning, deal scoring, and customer propensity; incorporate seasonality, exogenous drivers, and backtesting frameworks to ensure accuracy and robustness.
• Lead deep-dive analyses leveraging regression, causal inference, hypothesis testing, correlation analysis, and other statistical methods to surface actionable signals from complex, large-scale datasets.
• Architect and implement AI-first analyses and tooling using large language models, prompt engineering, retrieval-augmented generation (RAG), and related techniques to automate insight generation, surface qualitative signals at scale, and augment team capabilities.
• Own end-to-end forecasting and production pipelines powering GTM and Support planning workflows; ensure reliability, scalability, and business adoption of outputs.
• Develop and maintain prospect, deal health, archetype, and capacity models that inform GTM strategy, planning, and growth initiatives.
• Define the measurement framework by identifying, creating, and stewarding benchmarks and metrics that meaningfully represent growth, engagement, and success outcomes.
• Communicate complex analyses with executive-ready narratives to drive decisions at the senior leadership level.
• Collaborate cross-functionally with Systems & Engineer, GTM Operations, Rev Ops & Planning, Product, Business Intelligence, Data Science, and Finance to ensure analytical solutions are integrated, scalable, and trusted.

Job description

*At the company, we value the unique backgrounds, experiences and perspectives each the company (we call ourselves Klaviyos) brings to our workplace each and every day. We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements.

Summary

the company is looking for a Lead Data Science Analyst to join our GTM Strategic Analytics & Insights team. In this role, you will serve as a senior individual contributor at the intersection of advanced data science, AI/LLM-driven innovation, and Go-to-Market strategy. You will build and maintain sophisticated predictive and inferential models, conduct deep-dive statistical analyses, and develop AI-first solutions that unlock meaningful insights across the pre and post Sales Customer lifecycle.

The successful candidate will partner closely with GTM leadership to shape how the company understands, measures, and accelerates new business and customer outcomes; from pre-sales motion through onboarding, expansion and retention. You will operate with a strong bias toward AI-augmented workflows and bring a modern, LLM-aware approach to every analytical challenge.

The ideal candidate is intellectually curious, strategically minded, and energized by hard problems. They bring deep technical fluency across the full data science stack, a demonstrated ability to influence senior stakeholders through clear storytelling, and a genuine commitment to building AI-first solutions in a fast-moving SaaS environment.

How You Will Make a Difference

• Build and maintain advanced models: Build and maintain advanced predictive and time-series models: design, train, deploy, and monitor models across use cases such as demand forecasting, capacity planning, deal scoring, and customer propensity; incorporate seasonality, exogenous drivers, and backtesting frameworks to ensure accuracy and robustness

• Apply statistical rigor: lead deep-dive analyses leveraging regression, causal inference, hypothesis testing, correlation analysis, and other statistical methods to surface actionable signals from complex, large-scale datasets

• Develop AI/LLM-powered solutions: architect and implement AI-first analyses and tooling using large language models, prompt engineering, retrieval-augmented generation (RAG), and related techniques to automate insight generation, surface qualitative signals at scale, and augment team capabilities

• Own forecasting and decision systems: Own end-to-end forecasting and operational decision systems, including time-series demand forecasting, capacity planning models (e.g., Erlang-based staffing), and production pipelines that power GTM and Support planning workflows; ensure reliability, scalability, and business adoption of outputs

• Drive customer intelligence: develop and maintain prospect, deal health, archetype, and capacity models that inform GTM strategy, planning, and growth initiatives

• Define the measurement framework: identify, create, and steward benchmarks and metrics that meaningfully represent growth, engagement, and success outcomes

• Communicate with impact: distill complex analyses into clear, cohesive narratives with executive-ready materials that drive decisions at the senior leadership level

• Collaborate cross-functionally: partner with Systems & Engineer, GTM Operations, Rev Ops & Planning, Product, Business Intelligence, Data Science, and Finance to ensure analytical solutions are integrated, scalable, and trusted

Who You Are

• 6+ years of professional experience in an advanced analytics or data science role; SaaS experience strongly preferred

• Deep expertise in statistical inference and modeling, including supervised techniques (regression, classification, gradient boosting, decision trees) and unsupervised techniques (clustering, PCA, anomaly detection, topic modeling)

• Hands‑on experience designing and deploying AI/LLM‑based solutions, including prompt engineering, fine‑tuning, RAG pipelines, or LLM‑integrated analytics workflows; you approach new problems with an AI‑first mindset

• Familiarity and experience with distributed coding projects, including using Git for code management.

• Advanced proficiency in Python (pandas, numpy, scikit-learn, xgboost, statsmodels, and LLM/AI libraries such as LangChain, OpenAI SDK, or HuggingFace) and SQL; working knowledge of DBT

• Own and scale end-to-end data pipelines, including orchestration with Airflow and transformation/modeling with dbt; design reliable, testable, and modular workflows that support production-grade analytics and machine learning use cases, with a focus on performance, data quality, and maintainability.

• Develop and iterate on time‑series forecasting frameworks using approaches such as ARIMA/SARIMAX, ETS, MSTL, and machine learning‑based models; evaluate performance through rigorous backtesting and continuously improve model accuracy and business applicability

• Experience building data visualizations and dashboards across platforms such as Tableau, ThoughtSpot, matplotlib, seaborn, plotly, or similar tooling.

• Strong project ownership: experienced operating to a roadmap, managing milestones and deliverables, and delivering high‑quality work product in a timely manner

• Comfortable with autonomy and ambiguity, with a proactive orientation toward identifying and solving problems before they're fully defined

• Excellent written and verbal communication skills, including experience preparing materials for executive audiences

Massachusetts Applicants:It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Our salary range reflects the cost of labor across various U.S. geographic markets. The range displayed below reflects the minimum and maximum target salaries for the position across all our US locations. The base salary offered for this position is determined by several factors, including the applicant’s job‑related skills, relevant experience, education or training, and work location.

In addition to base salary, our total compensation package may include participation in the company’s annual cash bonus plan, variable compensation (OTE) for sales and customer success roles, equity, sign‑on payments, and a comprehensive range of health, welfare, and wellbeing benefits based on eligibility.

Your recruiter can provide more details about the specific salary/OTE range for your preferred location during the hiring process.

Base Pay Range For