Data Scientist - Pricing Lititz, PA Job Description Job Summary Webstaurant Store, the world’s largest online restaurant supply company, is looking for a full-time Data Scientist to join the Data Science team. The Data Scientists are responsible for supplying statistical rigor to the organization’s analytics projects, aimed at discovering actionable insights and opportunities for growth and optimization. This role can be remote in some US states (See below for remote work requirements) or based in one of our offices (Lititz, PA or Tampa, FL). Remote Work Qualifications - Access to a reliable and secure high-speed internet connection. Cable or fiber internet connections (at least 75mbps download/10mbps upload) are preferred, as satellite connections often cannot support the technologies used to perform day-to-day tasks. - Access to a home router and modem. - A dedicated home office space that is noise- and distraction-free. The space should have strong wireless connection or a wired Ethernet connection (wired connection is preferred, if possible). - A valid, physical address (apartment, suite, etc.). PO Boxes are not supported, as a physical address is required for you to receive your computer equipment. - The desire and ability to work and communicate with other team members via chat, webcam, etc. - Legal residents of one of the following states: (AK, AL, AR, AZ, CT, DE, FL, GA, IA, ID, IN, KS, KY, LA, MD, ME, MI, MN, MO, MS, NC, ND, NH, NM, NV, OH, OK, PA, SC, SD, TN, TX, UT, VA, VT, WI, WV, and WY). We only accept W-2 candidates, H-1B sponsorship is not available. Responsibilities Responsibilities include, but are not limited to: - Advising on analysis and modeling techniques, selecting the best fit for structured & unstructured, complex data, and developing custom analytics models to generate insights that drive value for our customers and unlock competitive advantage for our organization. - Collaborating with our analytics engineers to gather the right information from various sources so that you can implement advanced statistical methodologies and design interventions to optimize our business performance. - Conducting exploratory analysis including hypothesis testing, statistical inference, and statistical analysis (predictive and/or prescriptive). - Partnering with business and technical stakeholders to translate challenging retail business problems into state-of-the-art data science solutions. - Developing processes and tools that monitor, analyze and continuously improve model performance and data accuracy. - Work with other data scientists to design and implement experiments and glean actionable insights from experimental analyses.  - Defend and explain the validity of predictive/ML models to those without a background in data science or statistics. - Actively research new tools and technologies, staying on top of analytics news and best practices. Physical Requirements - Work is performed while sitting/standing and interfacing with a personal computer. - Requires the ability to communicate effectively using speech, vision, and hearing. - Requires the regular use of hands for simple grasping and fine manipulations. - Requires occasional bending, squatting, crawling, climbing, and reaching. - Requires the ability to occasionally lift, carry, push, or pull medium weights, up to 50lbs. Qualifications Experience - Minimum 2 years experience applying data science to pricing and demand problems in ecommerce, retail, or foodservice environments. - Proven ability to build and analyze price response curves or similar models to identify optimal pricing across a wide range of products. - Experience using data to inform pricing strategy and day-to-day pricing decisions, even if not the final decision owner. - Strong understanding of price elasticity, demand forecasting, and trade-offs between margin, volume, and customer acquisition. - Demonstrated ability to identify strategic low-priced items that drive customer traffic, alongside optimizing prices for both low and high AOV products. - Comfortable working with large SKU catalogs and messy real-world data to deliver actionable pricing insights. - Ability to partner closely with merchants, and other teams to translate model outputs into business decisions. - Advanced Python and SQL skills Education This role does not require a degree. We value relevant skills and experience and alignment with our core values above all else. Desired Traits & Skills The ideal candidate will possess the following qualities:   - You Communicate Effectively: Ability to explain ideas simply and confidently to team members both written and verbally.   - You have an Entrepreneurial Spirit: Takes it upon themselves to find ways to add value to the team and business. They are self-motivated and creative in their quest to find actionable insights and new solutions. They can often be found saying “What if we tried this?” or “Maybe this is a better way to do it?” They have a knack for overcoming obstacles.  - You Desire to Grow: Constantly seek to improve themselves and expand their professional knowledge and skill set.  - You’re an inquisitive, out-of-the box thinker who’s continually on the lookout for opportunities to improve and innovate data science solutions. - You have consistently high standards; your passion for quality is inherent in everything that you do. - Familiarity with a variety of supervised/unsupervised/reinforcement learning methods. - Demonstrable portfolio (git repos, kaggle competitions, etc) of machine learning projects. - You have proven ability as a full stack data scientist who develops, experiments, optimizes, and scales models for the production environment. - You connect the how and why, using your knowledge of data science theories and methodologies to derive the best approach that is fit-for-purpose.

• Designs and develops scalable solutions using AI tools and machine-learning models. • Performs research and testing to develop machine learning algorithms and predictive models. • Utilizes big data computation and storage tools to create prototypes and datasets. • Conducts model training and evaluation. • Integrates, tests, tunes, and monitors solutions. • Participates in model brainstorming conversations with potential internal customers interested in AI/ML capabilities. • Analyzes use cases of ML algorithms and applies findings to enable business decisions by deriving insights through data visualization. • Writing moderately complex SQL and Python/R code to extract data from databases and data sources. • Explores and visualizes data to verify data quality and ensure data quality via data cleaning. • Builds ML/AI models using common methods within R and Python. • Analyzes ML algorithms that could be used to solve problems and rank them by success probability. • Develops logging, alerting, and strategies for handling model errors. • Produces fairness review for each developed model. • Sets up continuous integration/continuous deployment (CI/CD) pipelines used for model automation. • Produces clean & readable code that has been correctly unit tested and optimized for performance. • Completes deployment integration testing to ensure seamless deployment. • Maintains and supports AI/ML patterns by reviewing and solving issues and running ML/AI models. • Assists in leading team-wide initiatives that help develop templates and define best practices to improve model building and deployment workflow.

• The Clinical Data Manager (or Senior Clinical Data Manager, based on experience) will lead database development and management efforts — encompassing EDC, eTMF, and CTMS systems. • This role requires deep expertise in clinical data management and system build, as well as proficiency in data visualization. • The ideal candidate will have demonstrated hands-on experience designing, building, implementing, and maintaining clinical data systems from the ground up, ensuring high-quality data outputs that support regulatory submissions and cross-functional decision-making. • This individual will serve as the functional owner of all clinical data systems and infrastructure and will be expected to assess, revise, and strengthen existing SOPs and data management processes to meet regulatory and operational standards. • Lead development, implementation, and ongoing management of eTMF and CTMS systems in collaboration with Clinical Affairs, Regulatory Affairs, and IT stakeholders.

Role Description The Head of Data is a rare hybrid role built for a seasoned data professional who thrives at the intersection of technical depth and business partnership. This is a founding position — the first dedicated data hire at the company — and the individual who steps into it will be responsible for building the data function from the ground up: - Establishing strategy - Selecting tools - Architecting infrastructure - Delivering reporting and insights In the near term, this person will operate as a team of one, performing hands-on work across the full data stack: - Designing and building a data warehouse and ELT pipelines - Collaborating with business leaders to understand critical metrics - Developing dashboards and reports Over time, this role will evolve into a team leadership position, with the Head of Data hiring, building, and managing a dedicated team beneath them. The right candidate is senior enough to know exactly what “good” looks like and how to build it — and humble and hungry enough to build it themselves. This is emphatically not a role for someone who has moved past hands-on work; it is a role for someone who still loves the work and is energized by the opportunity to create something new. Strategic thinking and technical execution are equally required. Key Responsibilities - Data Strategy & Architecture - Define and own the company's data strategy — identifying priorities, sequencing the work, selecting appropriate tools and technologies, and building a roadmap for the data function's evolution. - Architect and implement a scalable data warehouse that consolidates data from disparate source systems into a single, reliable source of truth. - Make pragmatic tooling decisions that balance immediate business needs with long-term scalability. - Document the data architecture, data dictionary, and system design decisions to ensure institutional knowledge is captured from day one. - Data Engineering & Pipeline Development - Design and build ELT pipelines to extract and transform data from source systems into the data warehouse. - Develop and maintain data connections and integrations with upstream systems. - Establish and enforce data quality standards, naming conventions, and governance practices. - Monitor and maintain pipeline performance, proactively identifying and resolving data issues. - Analytics, Reporting & Dashboard Development - Engage directly with business stakeholders to identify and prioritize critical metrics, KPIs, and reporting views. - Translate stakeholder requirements into well-designed dashboards and reports using BI tools. - Define and standardize metric definitions across the organization. - Conduct exploratory and ad hoc analysis to surface trends, anomalies, and insights. - Validate dashboard outputs rigorously, taking personal ownership of accuracy. - Team Building & Function Development - Operate effectively as a team of one in the near term. - Develop a staffing and capability roadmap for the data function. - Recruit, hire, and develop team members over time. - Establish the processes, standards, and team culture for the data function. - Cross-Functional Partnership - Serve as the primary data partner for leaders across the organization. - Communicate technical concepts and analytical findings clearly to non-technical audiences. - Collaborate with Finance and FP&A to ensure data infrastructure supports financial reporting. - Maintain a prioritized backlog of data and reporting requests. Qualifications - 10+ years of professional experience in data engineering, analytics, or business intelligence. - Proven track record working as a generalist or hybrid data professional. - Experience building or significantly scaling a data function. - Strong proficiency in SQL and experience with ELT tools and frameworks. - Hands-on experience designing and implementing data warehouse or data lake architectures in cloud environments. - Experience building dashboards and reports in at least one modern BI tool. - Demonstrated experience working directly with business stakeholders. - Prior experience in a multi-site, operationally complex business is a plus. Requirements - Bachelor's degree in Computer Science, Information Systems, Statistics, Mathematics, Data Analytics, or a related technical or quantitative field required. - Advanced degree or relevant certifications are a plus.