Staff Data Scientist

Robots & Pencils is an applied AI engineering firm building the next frontier of business architecture. We design and ship AI co-workers that integrate into enterprise operations and deliver measurable results for our clients.

We're all in on AWS, combining deep UX capability with senior engineering talent to get AI into production fast and keep it there.

We’ve earned the trust of leaders across Consumer Products and Retail, Education, Energy, Financial Services, Healthcare, and Manufacturing and more, and earned a reputation as the nimble alternative to traditional global systems integrators. Founded in 2009, with delivery centers in Canada, the United States, Eastern Europe, and Latin America, we are smaller, faster, and more senior by design. Our teams average 15+ years of experience.

We move fast, sweat the details, and build things that actually ship.

Position Overview

We’re looking for a Principal Data Scientist to join a multi-disciplinary team focused on designing and implementing scalable and reliable approaches to support or automate decision making throughout the business. This role is ideal for an experienced data scientist who can apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear.

In this role, you will acquire data by building the necessary SQL / ETL queries and import processes through various company specific interfaces for accessing S3, Red Shift, and Spark storage systems. You’ll build relationships with stakeholders and counterparts, analyze data for trends and input validity, and implement models that comply with evaluations of computational demands, accuracy, and reliability.

Why This Role Matters

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 to45 days. That pace demands people who take ownership, lead with craft, and care deeply about what they put their name on.

What You’llDo

Craft & Delivery

• Design and implement scalable and reliable approaches to support or automate decision making throughout the business
• Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear
• Acquire data by building the necessary SQL / ETL queries and import processes through various company specific interfaces for accessing S3, Red Shift, 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
• 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…