• Lead the design, development, and validation of R/Python code to automate generation of analytical datasets and TLFs. • Translate SAPs and metadata specifications (YAML/CSV) into executable and reproducible code. • Build and validate R packages and data science tools supporting both exploratory and confirmatory analyses. • Implement and validate statistical models (e.g., MMRM, ANCOVA, logistic regression). • Collaborate with IT to integrate data science workflows within Databricks and CI/CD pipelines. • Collaborate across programming, biostatistics, and data standards functions. • Conduct peer code reviews, unit testing, and automated validation. • Mentor and guide team members in best practices for programming, validation, and automation.

• Scope and co-develop production-level data science projects with our customers across different industries and use cases • Help users discover and master the Dataiku platform via user training, office hours, and ongoing consultative support • Provide strategic input to the customer and account teams that help make our customers successful. • Provide data science expertise both to customers and internally to Dataiku’s sales and marketing teams • Lead technical data science projects pre-sales scoping and design appealing proposals • Flag technical and non-technical account risks (onboarding issues, performance pitfalls, timeline slippage) • Develop custom Python-based “plugins” in collaboration with Solutions, R&D, and Product teams, to enhance Dataiku’s functionality • Lead Data Scientist engagements: You will coordinate agile sprints, prioritize tasks, estimate effort, do backlog grooming • Run demo booth/tech talk duties at company public events (e.g. Everyday AI) • Lead Junior Data Scientist technical interview • Contribute to 2 internal assets (internal best practice or external blog post/project on the public gallery) per year

• Help clients maximize the value of their data across the full analytics lifecycle, including data querying and wrangling, data visualization and business intelligence (BI), predictive analytics, machine learning, and artificial intelligence • Support clients in defining information strategy, data architecture, and data governance • Implement enterprise analytics and data management solutions that enable actionable insights, reduce cost and complexity, increase trust and data integrity, and improve operational effectiveness • Lead and coordinate internal teams to deliver high‑quality, client‑focused solutions • Engage directly with clients and communicate confidently about data products, analytics methodologies, and industry trends • Operate effectively in a high‑visibility, client‑facing role within a dynamic consulting environment

It's fun to work in a company where people truly BELIEVE in what they're doing! Fullsteam is a leading provider of vertical software and embedded payments technology dedicated to helping businesses flourish by providing their customers with seamless experiences. With a dynamic and growing team of over 1,900 employees, we are committed to driving innovation and delivering best-in-class software and payment solutions that empower small and medium-sized businesses across numerous industries. Our purpose is to help our customers grow their businesses and delight their customers. Join us and be a part of a forward-thinking company that values growth, excellence, and the success of our clients. Data Science, Machine Learning & AI Intern – PIC Business Systems Business Unit Overview: PIC Business Systems is the leading provider of web-based ERP software solutions for the window covering manufacturing industry, commanding over 50% market share with a perfect implementation track record spanning 35+ years. Our flagship product, e-PIC One Enterprise, serves industry leaders including Hunter Douglas, Budget Blinds (800+ franchises via HFC), and Springs Window Fashions. PIC was acquired by Fullsteam in January 2025 and operates within the Home ERP group, bringing enterprise-grade capabilities to a stable, profitable business generating approximately $10.8M in annual revenue. PIC is at the forefront of AI adoption within Fullsteam, having deployed Claude Code across all 14 engineers (achieving a documented 33:1 ROI) and built PICasso—a custom AI-powered Support Assistant with 40+ tools built on Strands Agents SDK and FastMCP, deployed on AWS ECS Fargate and leveraging AWS Bedrock for multi-model agent orchestration. The team of 25+ employees spans engineering, support, implementation, and operations, operating in a fully remote environment with a culture defined by four core values: Win Together, Embrace Change, Don’t Report the News, and Own the Outcome. Job Summary: The Data Science, Machine Learning & AI Intern will be PIC’s first dedicated data science and AI agent development role, responsible for developing predictive models, building analytics pipelines, creating and enhancing AI agents on AWS Bedrock, and embedding ML-driven insights into PIC’s products and operations. Reporting directly to the President, this intern will have access to rich multi-tenant ERP datasets spanning hundreds of window covering manufacturers and hands-on involvement with PICasso’s production AI agent infrastructure, providing a unique opportunity to work across the full spectrum of applied AI—from statistical modeling to autonomous agent development—in an industry-specific SaaS context. This role is ideal for a graduate student or advanced undergraduate in statistics, data science, machine learning, or a related quantitative field who wants hands-on experience building production ML systems and AI agents in a real business environment. The intern will contribute to PIC’s AI strategy while gaining exposure to enterprise SaaS operations, manufacturing domain expertise, and cloud infrastructure on AWS. Primary Responsibilities: - Build, maintain, and enhance AI agents using AWS Bedrock, including designing agent tool schemas, implementing post-condition validation, and optimizing agent performance across PICasso’s multi-agent architecture - Develop, test, and deploy new PICasso agent capabilities using Strands Agents SDK and FastMCP, contributing to the 40+ tool ecosystem that powers customer support operations - Design, train, and validate machine learning models for customer attrition prediction, leveraging ERP usage patterns, support ticket history, billing data, and engagement signals across PIC’s multi-tenant MySQL databases - Build supply and demand forecasting models for window covering manufacturing, incorporating seasonality, material pricing trends, and historical order data to improve production planning accuracy - Develop and maintain ETL data pipelines to extract, transform, and load data from Aurora MySQL multi-tenant databases into analytics-ready formats - Create interactive customer analytics dashboards and PicRite reports that surface actionable insights for account management, customer success, and executive leadership - Integrate ML-driven pricing validation logic to detect anomalies and optimize franchise pricing across large dealer networks (e.g., Budget Blinds) - Conduct exploratory data analysis to identify patterns, trends, and opportunities within PIC’s extensive ERP dataset - Participate in agent quality audits (review_low_scores) and contribute to reducing hallucination rates and improving agent accuracy - Document all models, agents, assumptions, data sources, and methodologies; present findings to engineering leadership and stakeholders - Collaborate with engineering, support, and implementation teams to understand business context and ensure model and agent relevance Skills & Competencies: - Strong foundation in statistics, probability, and machine learning algorithms (regression, classification, clustering, time series forecasting) - Proficiency in Python with data science libraries (pandas, NumPy, scikit-learn, TensorFlow/PyTorch) - Experience with SQL and relational databases; ability to write complex analytical queries against large datasets - Familiarity with LLMs, prompt engineering, and AI agent frameworks (experience with AWS Bedrock, LangChain, or similar a plus) - Familiarity with data visualization tools and libraries (Matplotlib, Seaborn, Plotly, or similar) - Understanding of ETL pipeline design and data engineering fundamentals - Strong analytical thinking with the ability to translate business problems into data science and AI solutions - Excellent written and verbal communication skills; ability to explain technical findings to non-technical stakeholders - Self-motivated with the ability to work independently in a remote environment - Intellectual curiosity and willingness to learn domain-specific knowledge in manufacturing and ERP systems Minimum Qualifications: - Currently pursuing or recently completed a Master’s degree in Statistics, Data Science, Computer Science, Machine Learning, Mathematics, or a related quantitative field - Coursework or project experience in machine learning, statistical modeling, or predictive analytics - Proficiency in Python and SQL - Experience with at least one ML framework (scikit-learn, TensorFlow, PyTorch, or similar) - Portfolio or academic projects demonstrating applied data science or AI work (Kaggle competitions, research projects, agent prototypes, or capstone work acceptable) Preferred Qualifications: - Experience with AWS services (Bedrock, SageMaker, Glue, Athena, ECS, or similar) - Hands-on experience building or working with LLM-based agents, tool-use patterns, or multi-agent architectures - Graduate-level coursework or research in machine learning, NLP, or time series analysis - Familiarity with MySQL/Aurora MySQL in production environments - Exposure to multi-tenant SaaS data architectures - Experience with version control (Git/GitHub) and collaborative development workflows - Experience with MCP (Model Context Protocol), FastMCP, or similar agent tooling frameworks - Knowledge of manufacturing, supply chain, or ERP domains Fullsteam supports an inclusive workplace that values diversity of thought, experience, and background. Fullsteam is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, ancestry, age, physical or mental disability, sex, sexual orientation, gender identity/expression, pregnancy, veteran status, marital status, creed, status with regard to public assistance, genetic status or any other status protected by federal, state, or local law.