Data Scientist

Huron is a global consultancy that collaborates with clients to drive strategic growth, ignite innovation and navigate constant change. Through a combination of strategy, expertise and creativity, we help clients accelerate operational, digital and cultural transformation, enabling the change they need to own their future. 

Join our team as the expert you are now and create your future.

Huron is a global consultancy that collaborates with clients to drive strategic growth, ignite innovation, and navigate constant change. We're seeking a Data Science Manager to join the Data Science & Machine Learning team in our Commercial Digital practice, where you'll lead advanced analytics initiatives that transform how Fortune 500 companies make decisions across Financial Services, Manufacturing, Energy & Utilities, and other commercial industries.
Managers play a vibrant, integral role at Huron. Their invaluable knowledge reflects in the projects they manage and the teams they lead. Known for building long-standing partnerships with clients, they collaborate with colleagues to solve their most important challenges. Our Managers also spend significant time mentoring junior staff on the engagement team—sharing expertise, feedback, and encouragement. This promotes a culture of respect, unity, collaboration, and personal achievement.
This isn't a reporting role or a dashboard factory—you'll own the full analytics lifecycle from hypothesis formulation through insight delivery, while leading and developing a team of data scientists and analysts. You'll work on problems that matter: experimental designs that validate multi-million-dollar strategies, predictive models that surface hidden patterns in complex data, and deep learning pipelines that extract signal from unstructured text, images, and time-series. Our clients are Fortune 500 companies looking for partners who can find the signal in the noise and tell the story that drives action.
The variety is real. In your first year, you might lead a customer segmentation and lifetime value analysis for a financial services firm, design and analyze a pricing experiment for a global manufacturer, and build an agentic anomaly detection system for a utility company's operational data—all while developing the next generation of data science talent at Huron. If you thrive on rigorous analysis, clear communication of complex findings, and building high-performing teams, this role is for you.

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. You've framed problems, developed hypotheses, analyzed data, and delivered insights that created measurable impact.
• Experience leading and developing technical teams—including coaching, mentorship, methodology review, and performance management. Demonstrated ability to build high-performing teams and develop junior talent.
• Strong Python and SQL programming skills with deep experience in the data science ecosystem (Pandas, NumPy, Scikit-learn, statsmodels, visualization libraries). Comfortable writing production-quality code, not just notebooks.
• 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. You know when ML approaches add value over classical methods, and how to integrate them into rigorous analytical workflows.
• Proficiency with data platforms: Microsoft Fabric, Snowflake, Databricks, or similar cloud analytics environments. You're comfortable working with large datasets and can optimize queries for performance.
• 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. This is non-negotiable.
• 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.

preferences:

• 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, etc.), or uncertainty quantification in business contexts.
• Strong visualization and data interface design and development skills using programmatic visualization libraries (Plotly, Altair, D3). Proficiency with AI-assisted rapid data application development using Cursor, Lovable, v0, etc.
• 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.

Position Level

Manager

Country

India