Data Scientist

VAST Data is looking for a Data Scientist (Sales) to join our growing team

This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.

"VAST's data management vision is the future of the market." - Forbes

VAST Data is the data platform company for the AI era. We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make them available for real-time data analysis and AI training and inference. Designed from the ground up to make AI simple to deploy and manage, VAST takes the cost and complexity out of deploying enterprise and AI infrastructure across data center, edge, and cloud.

Our success has been built through intense innovation, a customer-first mentality and a team of fearless VASTronauts who leverage their skills & experiences to make real market impact. This is an opportunity to be a key contributor at a pivotal time in our company's growth and at a pivotal point in computing history.

Overview:

VAST is committed to leveraging data to drive strategic decisions and improve business outcomes. We are seeking an experienced Data Scientist focused on Sales to join our team. The successful candidate will leverage advanced analytical techniques, machine learning, and statistical modeling to drive critical insights that optimize our sales strategies, improve performance, and maximize revenue. This role is essential for transforming raw sales data into actionable business recommendations. We're seeking a builder who thrives on transforming complex sales data into strategic, actionable intelligence that directly fuels revenue growth and optimizes our go-to-market (GTM) strategy. This role will conduct deep-dive analysis on the full sales funnel, pipeline, and work to enhance our forecasting.

Essential Duties and Responsibilities

• Predictive Modeling: Develop, deploy, and maintain predictive models (e.g., lead scoring, churn prediction, sales forecasting, propensity-to-buy) to enhance sales effectiveness and efficiency
• Sales Strategy & Optimization: Conduct deep-dive analysis on the full sales funnel—from initial lead to closed-won deal—to identify bottlenecks, measure sales rep productivity, and optimize resource allocation across different territories and segments.
• Pipeline & Deal Analysis: Analyze complex sales data (e.g., CRM data, pipeline, account executive activity) to identify key drivers of sales performance and potential areas for growth. Analyze deal dynamic to provide recommendations that improve sales velocity.
• Cross-Functional Collaboration: Collaborate closely with Sales Operations, Marketing, Finance and executive leadership to translate business questions into analytical frameworks and deliver data-driven recommendations.
• Communication: Delivers analytics that answer key business questions and deliver actionable insights. Distill complex analytical findings into clear, compelling narratives and visualizations for executive leadership, Sales VPs, and frontline managers using tools like Tableau.
• A/B Testing & Experimentation: Design and analyze sales experiments to rigorously measure impact and drive continuous GTM improvement.

Requirements

• Master's degree or Ph.D. in a quantitative field such as Data Science, Statistics, Computer Science, Economics, or a related discipline.
• 3-5 years of professional experience in a Data Scientist role, with a strong focus on Sales Analytics, Commercial Analytics, or Revenue Operations function, preferably within a SaaS or Enterprise software environment.
• Expert proficiency in SQL for data extraction, manipulation, and optimization
• Fluency in Python or R for statistical modeling and data manipulation
• Experience with Machine Learning techniques (regression, classification, clustering, and time series analysis) and deploying models into a production environment
• Familiarity with data visualization tools (e.g., Tableau, Power BI, Looker).
• Domain Knowledge: A strong understanding of B2B sales cycles, SaaS business metrics (e.g., ARR, LTV, CAC, logo retention), and the data structures within major CRM platforms (e.g., Salesforce).
• Ability to translate business objectives into testable hypotheses and communicate results clearly to non-technical business stakeholders.
• Ability to thrive in a fast-paced, dynamic environment and manage multiple priorities effectively
• Travel: Minimal travel required (approximately 10% or less annually)

Qualifications

• A relentless drive and a customer-first mentality are essential.
• An attention to detail that ensures accuracy and reliability in findings that leads to trust and credibility with stakeholders.
• The ability to break down complex problems, identify patterns, and derive meaningful insights from data.
• Intellectual curiosity with a natural desire to explore data and ask questions that lead to deeper insights.
• The ability to convey complex data insights clearly and effectively to both technical and non-technical stakeholders.
• Ability to manage multiple projects and deadlines with prioritizing tasks.
• Ability to thrive in a culture of transparency and direct feedback.