Summary

Klaviyo 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 Klaviyo 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 & Engineering, 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

Xometry is seeking a Principal Data & ML Scientist to join our Generative AI team. The ideal candidate will have a passion for advancing machine learning and generative AI capabilities, particularly for fine-tuning generative and language models, multimodal document understanding, and structured data extraction. This person will leverage their expertise in generative models and data science to develop and optimize innovative AI-driven solutions that enhance Xometry's service offerings.

Responsibilities: 

• Provide technical leadership to the Generative AI team, setting technical direction, defining best practices, and ensuring the team follows industry standards in AI and ML development.
• Lead strategic planning and roadmap development for generative AI initiatives, identifying high-impact projects and aligning them with Xometry’s business objectives.
• Develop and deploy generative AI models and large language models (LLMs) for multimodal document processing, focusing on extracting structured data from technical drawings, purchasing orders, and other complex documents.
• Lead the exploration and development of innovative text and image-based data processing solutions, including training and fine-tuning generative and language models.
• Design and implement efficient workflows for data preparation, cleaning, and augmentation to support the training of generative AI models.
• Utilize cloud platforms (e.g., Amazon Web Services) for large-scale data processing, model training, and deployment.
• Collaborate with cross-functional teams, including engineering and business teams, to align generative AI solutions with business needs and drive impactful applications.
• Mentor and guide team members on advanced machine learning techniques, model architecture design, and problem-solving strategies to elevate the team’s technical capabilities.
• Continuously experiment and iterate on model performance, tuning architectures and parameters to improve accuracy and efficiency in a fast-paced, agile environment.
• Stay updated with the latest research in generative AI, deep learning, and multimodal data processing, incorporating best practices and advancements into model development.

Qualifications:

• A bachelor’s degree is required, but an advanced degree (M.S. or PhD) in computer science, machine learning, AI, or a related field is highly preferred.
• 7+ years of experience in data science and machine learning, focusing on generative models, LLMs, or computer vision.
• Expertise in large-scale language and vision models (e.g., Transformers, GPT, VLMs).
• Experience with multimodal data processing (e.g., combining text, image, and 3D data).
• Proficient in Python, including key libraries such as PyTorch, TensorFlow, pandas, and numpy.
• Strong background in probability, statistics, and optimization techniques relevant to generative modeling.
• Familiarity with cloud computing resources and tools for model training and deployment (e.g., AWS SageMaker).
• Familiar with software engineering principles, including version control, reproducibility, and continuous integration.
• Experience in the manufacturing, supply chain, or similar industries is a plus.

The estimated base salary range for new hires into this role is $164,000- $213,000 annually + annual bonus depending on factors such as job-related skills, relevant experience, and location. We also offer a competitive benefits package, including 401(k) match, medical, dental and vision insurance; life and disability insurance; generous paid time off including vacation, sick leave, floating and fixed holidays, maternity and bonding leave; EAP, other wellbeing resources; and much more.

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