Senior Data Scientist

Join Smart IT in collaboration with our client to help millions of businesses Grow Better. We are seeking an experienced Senior Data Scientist to improve the efficiency of Sales and Customer Success teams through scalable AI/ML solutions. You will be joining a high-growth, high-powered team of Analytic Engineers, Data Scientists, and ML Engineers that deeply values intellectual curiosity, collaboration, and business impact. Team: The team consists of Data Scientists and PM + Support teams of Data Engineers and Analytics Objectives of this Role: - Build strong relationships with internal stakeholders, develop a deep understanding of their business problems, and act as a trusted advisor for AI solutions - Design and build machine learning and statistical models that improve the performance of go-to-market teams - Experiment with Generative AI (LLM/RAG) as potential accelerants - Identify and mature data sources that will further data science and business analytics - Use data to inform key business decisions and communicate findings effectively with senior leadership - Keep current with technical and industry developments Types of projects: - Renewal Complexity Score This project develops a data science scoring system to drive intelligent account prioritization and dynamic routing for customer renewals. The Renewal Complexity Score is a composite metric that integrates sophisticated commercial data (e.g., custom terms, discounting, payment history) with standard customer health and risk signals. The score ensures human Contract Managers (CMs) focus on the most complex, high-risk renewals, while low-complexity accounts are automatically routed to efficient self-service or AI Agent experiences. This system requires robust feature engineering and predictive modeling to deliver measurable efficiency and improve retention. - Credit/Value Insights Engine The Credit/Value Insights project is building an intelligence platform to transform renewal conversations by quantifying customer value and consumption ROI. This platform processes credit usage and subscription data to develop proprietary models for calculating delivered value. It surfaces automated, real-time "Value Realization" insights and peer-based benchmarks directly within the CM's workflow. This is critical for enabling data-driven, value-based negotiation and identifying expansion opportunities, fundamentally driving profitable growth during the renewal cycle. Responsibilities: - Partner with stakeholders and cross-functional teams to identify business problems, scope technical solutions, and build execution plans in a consultative manner - Rapidly prototype solutions in an iterative manner, implementing user feedback throughout the development lifecycle - Expert knowledge on a breadth of machine learning techniques (classical, deep learning, GenAI) and a thorough understanding of the best approach to use for a given situation - Execute ad-hoc analytical experiments to rigorously test potential solutions and strategies, as well as identify potential business opportunities - Define metrics which prove business value of deployed systems - Partner with Engineers to build systems in a scalable and reusable manner - Query, organize, integrate and clean data from multiple sources including both structured and unstructured data - Mature the data science practice by contributing to initiatives such as improving internal feature stores or building new infrastructure capabilities - Evangelize and drive adoption of the various data and AI products that you develop - Mentor more junior data scientists and analysts Requirements: - 5+ years experience in data science with multiple models deployed in an operational setting - Expert level knowledge in SQL and python programming (experience with DBT a plus) - Proficient using version controls systems (git/github) - Experience measuring accuracy of Gen AI systems - Ability to effectively communicate data science concepts and results to non-technical audiences - Ability to use data to persuasively present to senior management to inform strategic decision making Bonus Points: - 2+ years of experience leading data science initiatives - Experience using a deep learning python framework (tensorflow, pytorch, etc) - Experience building natural language processing models - Experience prompt engineering and working with large language models (LLMs) - A continued curiosity for the understanding and implementation of new technologies, such as Generative AI - Familiarity with customer success, sales, or marketing is a plus English: C1