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:
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The team consists of Data Engineers / Data Scientists and PM
Responsibilities:
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Collaborate with stakeholders to translate business needs into technical solutions and define success metrics.
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Design, build, and deploy ML models, ensuring continuous improvement and production scalability.
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Analyze structured and unstructured data, integrate insights, and evaluate model performance.
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Implement data pipelines in collaboration with analytics engineers and deploy models in CI/CD environments.
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Communicate data science results to non-technical teams and leadership, aligning with business goals.
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Lead high-impact AI/ML initiatives, managing the model lifecycle from inception to deployment.
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Participate in code reviews, testing, and documentation activities, ensuring high quality and maintainability of the codebase
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Mentor junior Data Scientists to improve their coding proficiency, algorithmic efficiency and general knowledge of the rapidly evolving field
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Drive clear ROI in terms of sales and CS rep acceleration via data and AI
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Keep current with the research and trends in AI/ML/GAI, and contribute to the development of new algorithms and techniques
Requirements:
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5+ years experience in data science with multiple models deployed in an operational setting
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Industry experience with LLMs or RAG flows
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Expert knowledge of a breadth of machine learning/AI techniques and a thorough understanding of the best approach to use for a given situation
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Deep knowledge of programming and ML frameworks (Scikit-learn, TensorFlow, PyTorch, HuggingFace, etc.)
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Familiarity with Snowflake, SQL, as well as dbt
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Familiarity with CI/CD systems (e.g. GitHub Actions, Jenkins, CircleCI, etc.)
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Familiarity with standard ML deployment stack (Docker, Kubernetes, Spark, Dask, etc.)
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Proven track record of delivering high-impact ML/AI products
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Experience breaking down large projects into smaller components, managing a roadmap, and releasing early+often
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Ability to effectively communicate data science concepts and results to non-technical audiences
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Ability to use data to persuasively present to senior management to inform strategic decision-making
Bonus Points:
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Experience working with Kafka or other streaming data
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Prior experience supporting GTM teams or functions, especially in B2B SaaS companies
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Experience deploying enterprise-grade models in AWS
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Familiarity with vector databases
English:
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B2-C1
Example Projects:
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Rep & Customer Engagement Analysis: Leverage AI to analyze communications (calls, emails, chats) to identify customer pain points, improve retention, and optimize rep strategies.
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Text Summarization: Expand on current projects to deliver concise, systematic CRM summaries, providing key insights at the right time.
Examples of day-to-day tasks:
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Dig into a customer request, understand the need, and translate into concrete technical steps and a rough project plan with success criteria, milestones, dependencies, risks, etc
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Work with analytics engineers to create a data pipeline in dbt, train a model to solve a use case in the business, work with stakeholders to test model output and determine if it meets need, iterate on suggested improvements
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Work with our CI/CD, build, deployment, and scheduling system to put a model into production, including prior PRs with the team, validation of output
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Before and after a project, think through how we might be able to demonstrate ROI around a particular request in terms of metrics choice, goals, AB testing, rollout strategy, etc
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Do PRs with team, both in terms of having their code reviewed and reviewing others’ code