U.S. Venture-posted 2 months ago
Full-time • Senior
Remote • Appleton, WI
1,001-5,000 employees
Merchant Wholesalers, Nondurable Goods

The Senior Data Scientist will play a crucial role in leading efforts to design, develop, and enhance analytical tools that address complex business challenges. This position will drive high-value modeling initiatives and experimentation, ensuring analytical rigor and innovation at every stage. A critical focus of this position is the ability to operationalize solutions, embedding advanced analytics into core processes and delivering scalable, production-ready capabilities that create measurable business impact. The individual in this role will lead and influence technical direction within projects, mentor and develop junior team members, innovate and expand our suite of analytical solutions, and advance research in priority areas.

  • Apply data science fundamentals: data collection, cleansing, modeling, and visualization.
  • Develop solutions in Python and SQL to solve complex problems.
  • Perform advanced data analysis and hypothesis testing to validate assumptions and guide modeling decisions.
  • Apply modern software engineering principles for data science (CI/CD, Git, object-oriented programming, containerization).
  • Perform advanced statistical modeling techniques, including classification and regression (ML/AI).
  • Optimize model methodologies.
  • Develop and manage forecasting models.
  • Architect scalable, reliable model services with monitoring and retraining strategies.
  • Establish robust evaluation frameworks (bias and robustness checks, ablations, model cards).
  • Lead innovation and data research efforts for new concepts and technologies.
  • Coordinate and facilitate technical brainstorming and ideation sessions.
  • Build proof-of-concepts and prototypes to validate emerging approaches.
  • Advance research initiatives in areas such as LLM/RAG evaluation & safety, AI agent frameworks, generative AI applications, advanced optimization, and causal ML.
  • Develop reusable accelerators and standards to shorten time-to-value for future projects.
  • Mentor junior team members in innovative solution development.
  • Stay ahead of industry trends and proactively identify opportunities to integrate cutting-edge techniques into business processes.
  • Champion responsible AI practices in all innovation efforts.
  • Lead problem framing and EDA to ensure the right method for the problem.
  • Own full lifecycle: model → experiment → pilot → monitoring → decision/adoption.
  • Drive prioritization and trade-off decisions to balance accuracy, scalability, and time-to-value.
  • Deliver executive-ready decision briefs and technical documentation.
  • Collaborate with platform and product teams to ensure seamless integration and operational reliability.
  • Embrace mentorship of junior team members and code reviews; guide method selection and documentation.
  • Coordinate with Platform for business-critical productionization and SLO alignment.
  • Build strong relationships and establish credibility with stakeholders at all levels.
  • Bachelor's or Master's degree in Data Science, Data Analytics, Economics, Statistics, Computer Science or a related field involving problem solving and critical thinking, or equivalent work experience.
  • 5+ years working in data science-specific roles, with demonstrated experience in data modeling, statistical modeling, model deployment, and data management.
  • Proven project experience working in ML and experimentation; strong software design instincts and observability practices.
  • Expertise in Python and SQL, with the ability to develop production-quality code using modern software engineering practices.
  • Proven ability to translate complex results into clear decisions and trade-offs.
  • Demonstrated high-level business acumen with a supply chain, transportation, and/or energy background being preferred.
  • Strong communication skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.
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