About the role
At Artisan, we're creating AI Employees, called Artisans, and software which is sleek, easy to use, and replaces the endless stack of point solutions. We're starting with outbound sales and our AI BDR, Ava. Our platform contains every tool needed for outbound sales - B2B data, AI email sequences, deliverability optimization tools and so much more.
We're growing very rapidly (closing $xM in new ARR each month). We recently raised a $15M from top investors, and are looking for superstars to join us on our rocketship growth as we relentlessly work towards building a multi-billion dollar company
As a Data Scientist at Artisan, you'll work closely with our AI/ML Engineering team to develop data-driven insights and models that enhance our AI Employees' performance. You'll be responsible for analyzing complex datasets, identifying patterns, and delivering actionable intelligence that drives our autonomous agents' decision-making capabilities.
Key Responsibilities
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Design and implement data analysis pipelines to extract insights from customer interactions, sales performance, and market responses
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Develop sophisticated machine learning models to enhance our AI Employees' ability to personalize outreach and optimize engagement
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Create and refine metrics and KPIs to measure AI Employee performance and identify areas for improvement
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Partner with AI/ML Engineers to integrate statistical models and insights into our agentic systems
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Build predictive models to anticipate customer needs, optimize timing of outreach, and forecast conversion rates
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Analyze large datasets of B2B interactions to identify patterns and trends that can improve sales effectiveness
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Conduct A/B testing and experimental design to continuously improve our AI-driven features
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Develop dashboards and visualizations to communicate data insights to stakeholders across the organization
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Research and implement novel data science techniques to keep Artisan at the cutting edge of AI-powered sales
Qualifications
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3+ years of professional experience in data science, with a focus on NLP, recommendation systems, or behavioral modeling
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Strong statistical background with experience in experimental design, causal inference, and predictive modeling
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Proficiency in Python and SQL, with experience using data science libraries (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow)
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Experience with large language models, embeddings, and vector databases
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Familiarity with feature engineering techniques for machine learning models
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Knowledge of data visualization tools (Tableau, Power BI, or similar)
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Experience working with large, complex datasets and distributed computing frameworks
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Track record of translating data insights into business impact
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MS or PhD in Statistics, Computer Science, Mathematics, or related quantitative field preferred
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Excellent communication skills with ability to explain complex concepts to technical and non-technical stakeholders
Benefits
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Full-coverage medical, dental, and vision insurance.
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Equity options.
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Company off-sites and events.
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Food & drinks provided in-office.
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