Staff Data Scientist

The individual will report to the manager of the Go To Market Insights and Analytics team. The individual will primarily support the Go To Market team but must work cross-functionally across Field Sales, Sales Ops, Marketing, Product Management, Finance, and others.

Evaluate emerging AI technologies and recommend practical applications that improve business productivity, reporting, and decision-making

Lead the evolution of traditional business intelligence solutions into AI-powered analytics experiences leveraging LLMs and generative AI technologies

Design and implement automated reporting solutions that deliver insights through AI-generated narratives, HTML-based reporting experiences, and conversational analytics interfaces

Partner with business stakeholders to identify opportunities where AI can accelerate decision-making and improve access to actionable insights

Collaborate with the data warehouse team to ensure core business data is accessible, accurate, secure, and optimized

Design and maintain scalable semantic data models and row-level security (RLS) frameworks that support secure access to analytics and AI applications

Develop workflows and automation solutions using technologies such as Python, APIs, and orchestration platforms (e.g., n8n) to move data between enterprise systems

Integrate and enrich enterprise data using systems such as Salesforce, data warehouses, and other operational platforms

Identify gaps and quality issues within enterprise data and develop strategies to source, enrich, and validate information from multiple systems

Frame and break down complex business problems into key components, design analyses, generate insights, and recommend practical solutions

Drive strategic analytics, AI, and data science initiatives while partnering with cross-functional teams across Sales, Marketing, Product, Finance, and Operations

What Makes You a Qualified Candidate

Bachelor’s degree in computer science, mathematics, engineering, or another STEM field

7+ years of experience in analytics, data science, business intelligence, analytics engineering, or related technical disciplines

Strong communication skills with the ability to influence stakeholders across both technical and business functions

Expert-level SQL skills and experience working with large-scale enterprise datasets

Experience developing solutions using Python or similar programming languages

Experience building AI-enabled analytics solutions using LLMs, generative AI platforms, prompt engineering, retrieval approaches, or related technologies

Strong understanding of data architecture, semantic models, governance, and security principles including row-level security (RLS)

Experience integrating and consuming data through APIs and external platforms

Ability to translate business problems into scalable analytical and technical solutions

Experience building AI-powered business applications, automated reporting solutions, or LLM-enabled analytics experiences

Experience with workflow automation platforms such as n8n, Power Automate, or similar orchestration technologies

Experience developing applications, scripts, or data pipelines using Python or similar programming languages

Working knowledge of HTML, JSON, REST APIs, and modern web technologies

Experience integrating enterprise systems such as Salesforce, CRM platforms, marketing systems, and cloud data warehouses

Experience identifying and resolving enterprise data quality, completeness, and governance challenges

Experience with data science, statistical analysis, forecasting, machine learning, or advanced analytics projects

Experience in the technology industry preferred

Knowledge of modern AI architecture patterns including prompt engineering, retrieval augmented generation (RAG), vector search, and agent-based workflows preferred

Understanding of enterprise security and governance requirements when deploying AI solutions

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