Huron is seeking a Data Science Manager to drive strategic growth, ignite innovation, and navigate constant change for Fortune 500 companies in Financial Services, Manufacturing, Energy & Utilities, and other commercial industries.
Requirements
- 5+ years of hands-on experience conducting data science and advanced analytics—not just ad-hoc analysis, but structured analytical projects that drove business decisions.
- Strong Python and SQL programming skills with deep experience in the data science ecosystem (Pandas, NumPy, Scikit-learn, statsmodels, visualization libraries).
- Solid foundation in statistics and machine learning: hypothesis testing, regression analysis, classification, clustering, experimental design, causal inference, and understanding of when different approaches are appropriate for different questions.
- Experience with deep learning and modern neural architectures—understanding of transformer models, embeddings, transfer learning, and how to leverage foundation models for analytical tasks.
- Proficiency with data platforms: Microsoft Fabric, Snowflake, Databricks, or similar cloud analytics environments.
- Experience with Bayesian methods, probabilistic programming (PyMC, NumPyro, etc.), or uncertainty quantification in business contexts.
- Hands-on experience with deep learning frameworks (PyTorch, TensorFlow) and neural architectures—including transformers, attention mechanisms, and fine-tuning pretrained models for NLP, time-series, or tabular data applications.
Responsibilities
- Lead and mentor junior data scientists and analysts—provide technical guidance, review analytical approaches and code, and support professional development.
- Manage complex multi-workstream analytics projects—oversee project planning, resource allocation, and delivery timelines.
- Design and execute end-to-end data science workflows—from problem framing and hypothesis development through exploratory analysis, modeling, validation, and insight delivery.
- Lead development of both traditional statistical and modern AI-powered analyses—including regression, classification, clustering, causal inference, A/B testing, and modern deep learning approaches using embeddings, transformer architectures, and foundation models for text, time-series, and multimodal analysis.
- Build predictive and prescriptive models that drive business decisions—customer segmentation, churn prediction, demand forecasting, pricing optimization, risk scoring, and operational efficiency analysis for commercial enterprises.
- Translate complex analytical findings into actionable insights—create compelling data narratives, develop executive-ready presentations, and communicate technical results to non-technical stakeholders in ways that drive decisions.
- Serve as a trusted advisor to clients—build long-standing partnerships, deeply understand business problems, formulate the right analytical questions, and deliver insights that create measurable value.
Other
- Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, or related quantitative field (or equivalent practical experience).
- Willingness to travel approximately 30% to client sites as needed.
- Exceptional communication and data storytelling skills—ability to distill complex analyses into clear narratives, create compelling visualizations, lead client meetings, and build trusted relationships with executive audiences.
- Consulting experience or demonstrated ability to work across multiple domains and adapt quickly to new problem spaces.
- Master's degree or PhD in Statistics, Applied Mathematics, Economics, or related quantitative field.
