Robots and Pencils - Data Scientist
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Requirements
• Experience with handling and modeling data in the healthcare industry is a plus • AWS certifications, like Certified Data Engineer – Associate, strongly preferred • You’ll Do Well Here if You Are • A doer. You see something broken and fix it. You'd rather move on clarity than wait for certainty. • A doer. • A fast learner who knows you don't know everything. The AI landscape changes weekly. You're senior enough to know better and curious enough to keep learning anyway. • A fast learner who knows you don't know everything. • Direct in a way that makes the work better. You give honest feedback. You'd rather have the hard conversation than blow smoke. • Direct in a way that makes the work better. • Obsessed with craft. You know genius is in the details. You ship exceptional, not perfect, and you don't put your name on work you wouldn't stand behind. • Obsessed with craft. • Built for ownership. You honor commitments, admit mistakes fast, and back your teammates when a decision costs something. No handoffs, no finger-pointing. • Built for ownership. • All in. You treat clients' businesses like your own. You take the work seriously without taking yourself seriously. • All in. • Resourceful when the budget, timeline, or team is tight. Constraints don't slow you down. They sharpen you. • Resourceful when the budget, timeline, or team is tight. • Glad to be in the room with people who care as much as you do. Our teams average fifteen-plus years of experience. We hire people who push each other to do better work. • Glad to be in the room with people who care as much as you do.
Responsibilities
• Craft & Delivery • Design and implement scalable and reliable approaches to support or automate decision making throughout the business • Acquire data by building the necessary SQL / ETL queries and import processes through various company specific interfaces for accessing S3, RedShift, and Spark storage systems • Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies • Build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks • Validate models against alternative approaches, expected and observed outcomes, and other business defined key performance indicators • Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production • Implement and deploy state of the art machine learning algorithms under Gen AI, build prototypes, troubleshoot customer issues, and explore new solutions • Interact closely with customers and with the academic community to drive innovation and deliver tailored data science solutions • Collaboration & Communication • Build relationships with stakeholders and counterparts to understand business needs and translate them into data science solutions • Collaborate closely with engineering, analytics, AI, and product teams to align data science models and insights with broader business goals • Communicate findings and model results clearly to non-technical executive audiences, ensuring insights are actionable and understood • Leadership & Influence • Establish data science best practices and modeling standards that lift the quality and consistency of analytical work across the team • Mentor junior and mid-level data scientists, helping them grow their craft, confidence, and impact • Bring an AI-forward mindset to your daily work, using tools like Claude, Cursor, and other modern AI assistants to deliver higher-quality work at pace
Benefits
• At Robots & Pencils, we design AI systems for a human world. Our name says it all. Robots and pencils means engineering paired with creativity, because every agent we ship has to work for real people in real workflows. That balance is baked into how we operate. Every role here contributes directly to that mission. Here, you shape how AI systems integrate into enterprise operations, how teams move at real velocity, and how products create measurable impact for clients and the people they serve. We ship production-ready AI in 30 to 45 days. That pace demands people who take ownership, lead with craft, and care deeply about what they put their name on. • What You’ll Do • Craft & Delivery • Design and implement scalable and reliable approaches to support or automate decision making throughout the business • Acquire data by building the necessary SQL / ETL queries and import processes through various company specific interfaces for accessing S3, RedShift, and Spark storage systems • Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies • Build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks • Validate models against alternative approaches, expected and observed outcomes, and other business defined key performance indicators • Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production • Implement and deploy state of the art machine learning algorithms under Gen AI, build prototypes, troubleshoot customer issues, and explore new solutions • Interact closely with customers and with the academic community to drive innovation and deliver tailored data science solutions • Collaboration & Communication • Build relationships with stakeholders and counterparts to understand business needs and translate them into data science solutions • Collaborate closely with engineering, analytics, AI, and product teams to align data science models and insights with broader business goals • Communicate findings and model results clearly to non-technical executive audiences, ensuring insights are actionable and understood • Leadership & Influence • Establish data science best practices and modeling standards that lift the quality and consistency of analytical work across the team • Mentor junior and mid-level data scientists, helping them grow their craft, confidence, and impact • Bring an AI-forward mindset to your daily work, using tools like Claude, Cursor, and other modern AI assistants to deliver higher-quality work at pace • What You’ll Bring • What You’ll Bring • 10+ years of data scientist experience with a proven track record of solving complex business problems through data science • Bachelor’s degree in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field • Competency in data querying languages (e.g. SQL) and scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) • Experience with statistical models (e.g., logistic regression, supervised learning approaches) and a solid foundation in machine learning methods • Excellent communications skills with non-technical executive audiences, with the ability to translate complex models and findings into clear, actionable insights • 1+ year of hands-on experience with AI/ML technologies and modern machine learning frameworks • Demonstrated leadership and technical mentoring experience across a team or organization • Strong stakeholder communication skills with the ability to translate technical depth across audiences • Demonstrable, day-to-day usage and expert knowledge of AI-forward coding tools such as Claude and Cursor • Excellent problem-solving skills and the ability to navigate highly ambiguous technical and business challenges with sound judgment • Experience with advanced machine learning frameworks and cloud-based data science platforms is a plus
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