Lead Data Scientist (Startup) ($45,000 - $61,000) (USD)

## About the Role We are looking for an experienced and entrepreneurial Lead Data Scientist to join our founding team. This is a critical, high-impact role where you will design and build the core machine learning models that power our platform. You will be responsible for the entire data science lifecycle, from architecting forecasting algorithms to deploying optimization models that help our customers navigate real-world supply chain volatility. This is a hands-on role for a true data scientist, not a data engineer or a data analyst. You thrive in a "data-heavy" environment and are an expert at building predictive and prescriptive models to solve complex, high-stakes operational challenges. ## What You'll Do - Lead the design, development, and deployment of machine learning models to solve key supply chain challenges, including demand forecasting, inventory optimization, logistics/shipping optimization, and disruption modeling. - Partner with product, engineering, and leadership to translate complex customer problems into a clear data science roadmap. - Conduct in-depth exploratory analysis on large, complex datasets (e.g., historical sales, logistics data, weather patterns, market signals) to uncover actionable insights. - Establish the foundations of data science at the company, implementing best practices for modeling, code standards, and experimentation. - Develop novel approaches to quantify and predict the impact of "black swan" events like port closures, strikes, or extreme weather on customer supply chains. - Communicate complex findings and the value of our models to both technical and non-technical stakeholders, including key customers. - Own the end-to-end data science workflow, from feature engineering to model validation and monitoring in a production environment. ## Who You Are ### Required - 6+ years of professional experience in a data science or machine learning role. - Significant experience working in a fast-paced startup environment. You are comfortable with ambiguity, can prioritize for maximum impact, and work autonomously. - Proven track record of working with large-scale, data-heavy environments and delivering ML solutions that drive measurable business value. Direct experience in supply chain, logistics, manufacturing, or operations is a massive plus. - Deep expertise in statistical methods and a wide range of machine learning algorithms, particularly in time-series forecasting, optimization, and anomaly detection. - Strong proficiency in Python and its core data science libraries (e.g., scikit-learn, Pandas, NumPy, Prophet, optimization libraries like PuLP or Gurobi). - Expert-level SQL skills for complex data querying and manipulation. - Excellent problem-solving skills and the ability to turn ambiguous business challenges into a well-defined analytical framework. - An M.S. or Ph.D. is preferred in a quantitative field like Operations Research, Industrial Engineering, Computer Science, Statistics, or a related discipline. ## Why Join Us? - High Impact: Be a foundational member of our technical team and see your work directly solve critical, real-world problems for major industries. - Meaningful Equity: As an early and crucial team member, you'll have a significant stake in our success. - Complex Challenges: Work on fascinating and difficult problems at the cutting edge of AI and supply chain management. - Flexible Environment: We trust our team and offer a flexible work environment that supports your best work. ## About the Company At Nuel, Inc., we are dedicated to transforming supply chain management through innovative software solutions. As a venture-backed startup, our mission is to empower businesses to leverage data effectively for informed decision-making and driving profitability. We specialize in advanced data integration, machine learning, and AI-driven analytics to improve demand forecasting, production planning, and inventory management. While our roots are in agriculture, our adaptable solutions meet the needs of diverse industries, including manufacturing and logistics. Committed to sustainability, we help clients reduce their carbon footprint and uncover trends for a more resilient future.