• Build machine learning and AI solutions that support pricing, forecasting, and revenue management decisions in hospitality. • Analyze large, sometimes messy datasets to identify patterns, risks, and opportunities, and turn them into practical recommendations or product capability. • Write clean Python and SQL, working with data pipelines and analytical workflows to prepare, validate, and operationalize data. • Apply modern AI techniques, including LLMs and AI coding tools such as Claude Code, thoughtfully to accelerate prototyping, learning, and development while maintaining technical quality. • Partner closely with product, engineering, and cross-functional stakeholders to translate business problems into analytical solutions and communicate insights clearly.

• Own ongoing data entry in specified systems as demanded by the business • Enforce our data governance guidelines and suggest new processes and controls to improve our consistency • Develop an in-depth understanding of our systems and operate as an SME. This person will represent Master Data cross-functionally and will assist with onboarding and training new team members • Break down complex, multi-step projects into clear tasks that other associates can easily execute • Track project progress and communicate status updates to the Director and relevant stakeholders • Scope new projects as they come in, identifying what Master Data owns, what Master Data contributes to, and what tasks are owned by other teams • Support the creation of new processes that impact Master Data, even when Master Data is not the ultimate owner of that process • Represent the Director and the Master Data team in meetings when appropriate • Own the team’s short-term and long-term project tracking. This includes building tools that allow the team to measure progress as work is completed • Partner with Retail, Operations, Accounting, Finance, and IT to maintain master data including creation, modification, cleansing, and enrichment • Own quarterly audits of data integrity and accuracy • Support data integration initiatives in partnership with the M&A team • Partner with internal and external audit teams to document procedures, respond to follow-up questions, and assist with ongoing SOX documentation

• Lead, mentor, and scale a high-performing team of data engineers and data scientists • Define and drive the data architecture vision, technical standards, and best practices across client engagements • Champion AI/ML initiatives, identifying opportunities for automation, modelling, and intelligent activation • Oversee end-to-end delivery of data platforms, pipelines, and tooling across client projects • Ensure strong data governance, security, and compliance across all workflows • Collaborate with CRM, Growth, and Strategy teams to align technical delivery with business objectives • Partner with clients to translate business requirements into scalable technical solutions • Manage vendor and platform relationships across cloud, data warehouse, and CDP ecosystems • Optimise performance, reliability, and cost efficiency of data infrastructure and operations • Represent Massive Rocket’s data capabilities in client conversations, proposals, and strategic engagements

Role Description As a Machine Learning Data Scientist – Research Translation & Prototyping, you will work at the intersection of cutting-edge AI research and real-world application. You will partner with researchers, engineers, designers, and product stakeholders to evaluate emerging technologies, build rapid prototypes, and develop machine learning solutions that help transform experimental concepts into usable tools and experiences. This role is ideal for a hands-on builder who thrives in fast-paced, ambiguous environments and enjoys translating research, data, and novel ideas into measurable outcomes. Success requires strong technical expertise in machine learning and software engineering, the ability to design and execute experiments, and a passion for quickly validating new technologies through prototyping and evaluation. Key Responsibilities - Collaborate with research, engineering, and cross-functional teams to evaluate emerging AI and machine learning technologies and determine their practical value. - Design, develop, and implement machine learning models, AI-powered applications, and experimental systems. - Build rapid prototypes and proof-of-concept solutions to validate new technologies and research concepts. - Fine-tune, benchmark, validate, and improve machine learning models using real-world datasets. - Develop evaluation frameworks, benchmarks, and success metrics for AI systems, foundation models, generative AI solutions, multimodal experiences, and agent-based workflows. - Design and execute quantitative and qualitative experiments to assess model performance, user engagement, technology adoption, and overall effectiveness. - Analyze system requirements, document technical specifications, and develop software solutions aligned with project objectives. - Gather, process, and analyze data to generate actionable insights and support decision-making. - Evaluate, troubleshoot, and improve machine learning pipelines, AI systems, and software implementations. - Develop, test, and maintain software applications and supporting infrastructure. - Create and execute test plans, perform unit testing, and support quality assurance efforts. - Support deployment, validation, and post-implementation monitoring of solutions, resolving issues identified during testing and rollout. - Stay current with advancements in machine learning, generative AI, multimodal systems, agentic workflows, and related research areas to identify opportunities for innovation and application. Qualifications - Bachelor's degree in Computer Science, Computer Engineering, Data Science, Mathematics, Statistics, or a related technical field. - 5–7+ years of professional experience in machine learning, data science, applied AI, software engineering, or a related discipline. - Strong experience developing machine learning models and AI-powered solutions. - Demonstrated experience with data science methodologies, experimentation, model evaluation, and statistical analysis. - Hands-on software engineering experience, including coding, debugging, testing, and deployment. - Experience building data-intensive applications, machine learning systems, experimentation platforms, or AI-enabled products. - Strong programming skills and the ability to diagnose and resolve technical issues. - Experience evaluating, improving, and maintaining machine learning models, data pipelines, and AI applications. - Ability to quickly learn new technologies, adapt to changing priorities, and contribute effectively in ambiguous, fast-moving environments. - Strong communication skills with the ability to explain technical concepts and findings to both technical and non-technical audiences. - Experience working collaboratively across research, engineering, product, and business teams. Preferred Qualifications - Experience translating research concepts, academic publications, or emerging technologies into working prototypes and production-ready solutions. - Experience with foundation models, large language models (LLMs), generative AI systems, multimodal AI, agentic workflows, and retrieval-augmented generation (RAG). - Proven ability to rapidly prototype and iterate on ideas using modern AI development tools and AI-assisted coding workflows. - Experience designing evaluation frameworks, benchmarks, and success metrics for AI systems. - Familiarity with model fine-tuning, experimentation, model validation, and performance optimization techniques. - Experience working on research-driven initiatives or innovation-focused environments. - Ability to ramp up quickly on new projects and deliver meaningful results within short timelines. - Experience supporting end-to-end machine learning solution development, from experimentation through deployment and validation. - Demonstrated flexibility and success working across multiple research or product domains simultaneously. - Availability for a long-term engagement (12+ months preferred). Salary Range Pay ranges vary based on multiple factors including, without limitation, skill sets, education, responsibilities, experience, and geographical market. The pay range for this position reflects geographic based ranges for Washington state: $145,000- $155,000 USD annually. The salary/wage and job title for this opening will be based on the selected candidate’s qualifications and experience and may be outside this range. Benefits - Medical, dental, and vision coverage - Flexible Spending Account - 401k program - Competitive PTO offerings - Parental Leave - Opportunities for professional growth and development Equal Opportunity Employer Blueprint Technologies, LLC is an equal employment opportunity employer. Qualified applicants are considered without regard to race, color, age, disability, sex, gender identity or expression, orientation, veteran/military status, religion, national origin, ancestry, marital, or familial status, genetic information, citizenship, or any other status protected by law. If you need assistance or a reasonable accommodation to complete the application process, please reach out to: recruiting@bpcs.com Location Remote