Data Scientist (Associate)

Chicago, IL

Full-time

Hybrid

Entry Level

Huron is a global consultancy that collaborates with clients to drive strategic growth, ignite innovation, and navigate constant change. They are seeking a Data Scientist to join the Data Science & Machine Learning team, where the role involves conducting advanced analytics and building predictive models to transform decision-making for Fortune 500 companies. The position emphasizes ownership of the analytics lifecycle and effective communication of complex findings to stakeholders.

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Responsibilities

Design and execute end-to-end data science workflows—from problem framing and hypothesis development through exploratory analysis, modeling, validation, and insight delivery. Own the analytical approach and ensure conclusions are defensible
Develop 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
Rapidly build interactive data stories and applications—deliver insights through compelling visualizations and user-friendly interfaces that stakeholders can explore
Translate complex analytical findings into actionable insights—create compelling data narratives, develop presentation-ready deliverables, and communicate technical results to non-technical stakeholders in ways that drive decisions
Collaborate directly with clients and senior team members—understand business problems, formulate the right analytical questions, and contribute to insights that create measurable value

Qualification

Required

2+ years of hands-on experience conducting data science and advanced analytics—not just ad-hoc analysis, but structured analytical projects that drove business decisions. You've framed problems, developed hypotheses, analyzed data, and delivered insights that created measurable impact
Strong Python and SQL programming skills with deep experience in the data science ecosystem (Pandas, NumPy, Scikit-learn, statsmodels, visualization libraries). Comfortable writing clean, reproducible code, not just notebooks
Solid foundation in statistics and machine learning: hypothesis testing, regression analysis, classification, clustering, experimental design, and understanding of when different approaches are appropriate for different questions
Experience with deep learning and modern neural architectures—understanding of transformer models, embeddings, and how to leverage foundation models for analytical tasks. You know when ML approaches add value over classical methods
Proficiency with data platforms: Microsoft Fabric, Snowflake, Databricks, or similar cloud analytics environments. You're comfortable working with large datasets and can write efficient queries
Strong visualization and rapid data application development skills—proficiency with programmatic visualization libraries (Plotly, Altair) and AI-assisted rapid application development using Cursor, Lovable, v0, or similar tools. You can quickly build interactive data interfaces that bring analyses to life
Ability to communicate technical concepts to non-technical stakeholders and work effectively with cross-functional teams. Strong data storytelling skills are essential
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

Preferred

Experience in Financial Services, Manufacturing, or Energy & Utilities industries
Background in experimental design, A/B testing, and causal inference methodologies—including propensity score matching, difference-in-differences, or instrumental variables
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
Experience building AI-assisted analytical workflows—leveraging foundation model APIs, vector databases, and retrieval systems to accelerate insight extraction from unstructured data
Experience with Bayesian methods, probabilistic programming (PyMC, NumPyro), or uncertainty quantification in business contexts
Experience with time-series analysis, forecasting methods (ARIMA, Prophet, neural forecasting), and demand planning applications
Cloud certifications (Azure Data Scientist, Databricks ML Associate, AWS ML Specialty)
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

Benefit

Investment in your development.
We provide resources for continuous learning, conference attendance, and certification.

Huron is a global professional services firm that collaborates with clients to put possible into practice by creating sound strategies, optimizing operations, accelerating digital transformation, and empowering businesses and their people to own their future.

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