Qureos Mentor

Huron Consulting Group

<div><div>Huron is redefining what a global consulting organization can be. Advancing new ideas every day to build even stronger clients, individuals and communities. We&rsquo;re helping our clients find new ways to drive growth, enhance business performance and sustain leadership in the markets they serve. And, we&rsquo;re developing strategies and implementing solutions that enable the transformative change they need to own their future.<br>
<br>
As a member of the Huron corporate team, you&rsquo;ll help to evolve our business model to stay ahead of market forces, industry trends and client needs. Our accounting, finance, human resources, IT, legal, marketing and facilities management professionals work collaboratively to support Huron&rsquo;s collective strategies and enable real transformation to produce sustainable business results.<br>
<br>
Join our team and create your future.</div><div></div>
Huron is redefining what a global consulting organization can be. Advancing innovative ideas every day to build even stronger clients, individuals, and communities. We&rsquo;re helping our clients find new ways to drive growth, enhance business performance and sustain leadership in the markets they serve. And we&rsquo;re developing strategies and implementing solutions that enable the transformative change they need to own their future.<br>
As a member of the Huron corporate team, you&rsquo;ll help to evolve our business model to stay ahead of market forces, industry trends and client needs. Our accounting, finance, human resources, IT, legal, marketing and facilities management professionals work collaboratively to support Huron&rsquo;s collective strategies and enable real transformation to produce sustainable business results.<br>
<br>
Join our team and create your future.<br>
Huron&rsquo;s Resource Management (RM) team members are trusted strategic advisors to our business leaders, delivering solutions that balance the needs of our people, our company, and our clients. The team delivers high quality staffing solutions that ensure proper alignment of resources to projects, optimizes utilization, and supports career development for employees. We provide unique perspectives through data-informed insights and foster deep, collaborative, and consultative relationships with the stakeholders we engage.<br>
Specifically, the Resource Manager implements practical, seamless processes and systems to support resource allocation and planning that the business trusts and utilizes. They support all key business functions associated with managing the supply and demand of consultants for client engagements. They deliver utilization and forecasting insights that drive strategic business decisions and meet organizational business objectives. They also partner with other operational functions to drive future workforce planning.<br>
Key to success in this role is one&rsquo;s ability to establish and maintain credibility with practice / internal teams, develop and maintain a deep understanding of business offerings and effectively communicate at all levels throughout the organization. This position reports to the Resource Management Strategy Lead for their assigned team and interacts directly with business leaders and employees, Human Capital, Operations, IT and Procurement personnel.<br>
This role requires close collaboration with colleagues in the US and demands flexibility to work during evening IST hours to align with US working hours [till 11am CT].<div></div><div>
Job Description Summary</div><div>
Required:</div><ul><li>
Coordinate staffing assignments for consultants within your assigned area; understand project demand and match with resources based on availability, background, experience, and interests</li><li>
Develop and maintain understanding of business unit offerings to ensure better matching of skill sets and project needs</li></ul><ul><li>
Lead staffing calls for your assigned areas, participate in leading monthly new hire resource management orientations and bi-weekly RM team meetings (all RMs participate in leading calls)</li><li>
Establish and maintain credibility with practice/solution and internal teams to facilitate ongoing relationships and service delivery efforts</li><li>
Maintain staffing software/reporting and coordinate with other areas to ensure data is updated appropriately</li><li>
Effectively team and communicate with HR, Operations, Recruiting, L&amp;OE and other Resource Managers across the company</li><li>
Support internal RM process improvement efforts as needed and drive RMO initiatives across your assigned areas</li><li>
Review and recommend modifications to internal processes as needed for project control, operations review and business support.</li></ul><ul><li>
Reporting:</li></ul><ul><li>
Track and report utilization and provide reasoning for over/under utilization wherever applicable.</li><li>
Help track shadow and investment hours across industries and provide insight wherever possible</li><li>
Assist with scheduled and ad-hoc reporting and BU related insights</li></ul><div></div><div>
Qualifications</div><ul><li>
At least 3 &ndash; 5 years of work experience in resource management; experience in management consulting organizations highly preferred</li><li>
Huron requires a bachelor&rsquo;s degree in a field related to this position</li><li>
Experience in capacity planning and forecasting.</li><li>
Exceptional communication, influencing and analytical skills.</li><li>
Strong oral presentation, listening and influencing skills</li><li>
Proven collaboration skills</li><li>
Ability to adapt to flexi-working hours</li><li>
Experience with resource automation systems and software (Preferably Workday)</li><li>
High proficiency in Microsoft Office (Excel, Word, PowerPoint, SharePoint)</li><li>
Experience in reporting, with some familiarity with data analytics tools (i.e., Power BI)</li></ul><div></div><div>
Position Level</div>
Associate<div></div><div>
Country</div>
India</div>

Resource Management Associate

<div><div>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.<br>
<br>
Join our team as the expert you are now and create your future.</div><div></div>
Huron is a global consultancy that collaborates with clients to drive strategic growth, ignite innovation, and navigate constant change. We're seeking a Machine Learning Engineering Manager to join the Data Science &amp; Machine Learning team in our Commercial Digital practice, where you'll lead the design, development, and deployment of intelligent systems that solve complex business problems across Financial Services, Manufacturing, Energy &amp; Utilities, and other commercial industries.<br>
<br>
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. Remarkably versatile, our Managers also spend significant time mentoring junior staff on the engagement team&mdash;sharing expertise, feedback, and encouragement. This promote<br>
s a culture of respect, unity, collaboration, and personal achievement.<br>
<br>
This isn't a research role or a support function&mdash;you'll own the full ML solution lifecycle from problem definition through production deployment, while leading and developing a team of engineers and data scientists. You'll work on systems that matter: forecasting models that inform multi-million-dollar decisions, agentic AI systems that automate complex workflows, and operational ML solutions that transform how enterprises run. Our clients are Fortune 500 companies looking for partners who can deliver, not just advise.<br>
<br>
The variety is real. In your first year, you might lead an agentic demand forecasting system for a global manufacturer, oversee an intelligent knowledge processing pipeline for a financial services firm, and architect an energy grid demand simulation model for a utilities company&mdash;all while developing the next generation of ML talent at Huron. If you thrive on learning new domains quickly, shipping intelligent production systems, and building high-performing teams, this role is for you.<div></div><div>
What You'll Do</div><ul><li>
Lead and mentor junior ML engineers and data scientists&mdash;provide technical guidance, conduct code reviews, and support professional development. Foster a culture of continuous learning and high-quality engineering practices within the team.</li><li>
Manage complex multi-workstream ML projects&mdash;oversee project planning, resource allocation, and delivery timelines. Ensure projects meet quality standards and client expectations while maintaining technical excellence.</li><li>
Design and architect end-to-end ML solutions&mdash;from data pipelines and feature engineering through model training, evaluation, and production deployment. Make key technical decisions and own the overall solution architecture.</li><li>
Lead development of both traditional ML and generative AI systems, including supervised/unsupervised learning, time-series forecasting, NLP, LLM applications, RAG architectures, and agent-based systems using frameworks like Agent Framework, LangChain, LangGraph, or similar.</li><li>
Build financial and operational models that drive business decisions&mdash;demand forecasting, pricing optimization, risk scoring, anomaly detection, and process automation for commercial enterprises.</li><li>
Establish MLOps best practices&mdash;define and implement CI/CD pipelines, model versioning, monitoring, drift detection, and automated retraining standards to ensure solutions remain reliable in production.</li><li>
Serve as a trusted advisor to clients&mdash;build long-standing partnerships, understand business problems, translate requirements into technical solutions, and communicate results to both technical and executive audiences.</li><li>
Contribute to practice development&mdash;participate in business development activities, develop reusable assets and methodologies, and help shape the technical direction of Huron's DSML capabilities.</li></ul><div></div><div>
Required Qualifications</div><ul><li>
5+ years of hands-on experience building and deploying ML solutions in production&mdash;not just notebooks and prototypes. You've trained models, put them into production, and maintained them at scale.</li><li>
Experience leading and developing technical teams&mdash;including coaching, mentorship, code review, and performance management. Demonstrated ability to build high-performing teams and develop junior talent.</li><li>
Strong Python and JavaScript programming skills with deep experience in the ML ecosystem (NumPy, Pandas, Scikit-learn, PyTorch or TensorFlow, etc.) and proficiency with JavaScript web app development.</li><li>
Solid foundation in ML fundamentals: supervised and unsupervised learning, model evaluation, feature engineering, hyperparameter tuning, and understanding of when different approaches are appropriate.</li><li>
Experience with cloud ML platforms, particularly Azure Machine Learning, with working knowledge of AWS SageMaker or Google AI Platform. We're platform-flexible but Microsoft-preferred.</li><li>
Proficiency with data platforms: SQL, Snowflake, Databricks, or similar. You're comfortable working with large datasets and architecting data pipelines.</li><li>
Experience with LLMs and generative AI: prompt engineering, fine-tuning, embeddings, RAG systems, or agent frameworks. You understand both the capabilities and limitations.</li><li>
Excellent communication and client management skills&mdash;ability to communicate technical concepts to non-technical stakeholders, lead client meetings, and build trusted relationships with executive audiences.</li><li>
Bachelor's degree in Computer Science, Engineering, Mathematics, Physics, or related quantitative field (or equivalent practical experience).</li><li>
Willingness to travel approximately 30% to client sites as needed.</li></ul><div></div><div>
Preferred Qualifications</div><ul><li>
Experience in Financial Services, Manufacturing, or Energy &amp; Utilities industries.</li><li>
Background in forecasting, optimization, or financial modeling applications.</li><li>
Experience with deep learning frameworks such as PyTorch, Tensorflow, fastai, DeepSpeed, etc.</li><li>
Experience with MLOps tools such as MLflow and Weights &amp; Biases.</li><li>
Contributions to open-source projects or familiarity with open-source ML tools and frameworks.</li><li>
Experience building agentic AI systems using Agent Framework (or predecessors), LangChain, LangGraph, CrewAI, or similar frameworks.</li><li>
Cloud certifications (Azure AI Engineer, AWS ML Specialty, or Databricks ML Associate).</li><li>
Consulting experience or demonstrated ability to work across multiple domains and adapt quickly to new problem spaces.</li><li>
Master's degree or PhD in a quantitative field.</li></ul><div></div><div>
Why Huron</div><div>
Variety that accelerates your growth. In consulting, you'll work across industries and problem types that would take a decade to encounter at a single company. Our Commercial segment spans Financial Services, Manufacturing, Energy &amp; Utilities, and more&mdash;each engagement is a new domain to master and a new system to ship.</div><div>
Impact you can measure. Our clients are Fortune 500 companies making significant investments in AI. The models you build will inform real decisions&mdash;production schedules, pricing strategies, risk assessments, capital allocation. You'll see your work drive outcomes.</div><div>
A team that builds. Huron's Data Science &amp; Machine Learning team is a close-knit group of practitioners, not just advisors. We write code, train models, and deploy systems. You'll work alongside engineers and data scientists who understand the craft and push each other to improve.</div><div>
Investment in your development. We provide resources for continuous learning, conference attendance, and certification. As our DSML practice grows, there's significant opportunity to take on technical leadership, shape our capabilities, and advance to senior leadership roles.</div><div></div><div>
Position Level</div>
Manager<div></div><div>
Country</div>
United States of America</div>

Machine Learning Engineer (Manager)

<div><div>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.<br>
<br>
Join our team as the expert you are now and create your future.</div><div></div>
Huron is a global consultancy that collaborates with clients to drive strategic growth, ignite innovation, and navigate constant change. We're seeking a Machine Learning Engineer to join the Data Science &amp; Machine Learning team in our Commercial Digital practice, where you'll design, build, and deploy intelligent systems that solve complex business problems across Financial Services, Manufacturing, Energy &amp; Utilities, and other commercial industries.<br>
<br>
This isn't a research role or a support function&mdash;you'll own the full ML solution lifecycle from problem definition through production deployment. You'll work on systems that matter: forecasting models that inform multi-million-dollar decisions, agentic AI systems that automate complex workflows, and operational ML solutions that transform how enterprises run. Our clients are Fortune 500 companies looking for partners who can deliver, not just advise.<br>
<br>
The variety is real. In your first year, you might build an agentic demand forecasting system for a global manufacturer, deploy an intelligent knowledge processing pipeline for a financial services firm, and architect an energy grid demand simulation model for a utilities company. If you thrive on learning new domains quickly and shipping intelligent production systems, this role is for you.<div></div><div>
What You'll Do</div><ul><li>
Design and build end-to-end ML solutions&mdash;from data pipelines and feature engineering through model training, evaluation, and production deployment. You own the outcome, not just a piece of it.</li><li>
Develop both traditional ML and generative AI systems, including supervised/unsupervised learning, time-series forecasting, NLP, LLM applications, RAG architectures, and agent-based systems using frameworks like Agent Framework, LangChain, LangGraph, or similar.</li><li>
Build financial and operational models that drive business decisions&mdash;demand forecasting, pricing optimization, risk scoring, anomaly detection, and process automation for commercial enterprises.</li><li>
Create production-grade APIs and services (FastAPI, Flask, or similar) that integrate ML capabilities into client systems and workflows.</li><li>
Implement MLOps practices&mdash;CI/CD pipelines, model versioning, monitoring, drift detection, and automated retraining to ensure solutions remain reliable in production.</li><li>
Collaborate directly with clients to understand business problems, translate requirements into technical solutions, and communicate results to both technical and executive audiences.</li></ul><div></div><div>
Required Qualifications</div><ul><li>
2+ (3+ years for Sr. Associate) years of hands-on experience building and deploying ML solutions in production&mdash;not just notebooks and prototypes. You've trained models, put them into production, and maintained them.</li><li>
Strong Python and JavaScript programming skills with deep experience in the ML ecosystem (NumPy, Pandas, Scikit-learn, PyTorch or TensorFlow, etc.) and proficiency with JavaScript web app development.</li><li>
Solid foundation in ML fundamentals: supervised and unsupervised learning, model evaluation, feature engineering, hyperparameter tuning, and understanding of when different approaches are appropriate.</li><li>
Experience with cloud ML platforms, particularly Azure Machine Learning, with working knowledge of AWS SageMaker or Google AI Platform. We're platform-flexible but Microsoft-preferred.</li><li>
Proficiency with data platforms: SQL, Snowflake, Databricks, or similar. You're comfortable working with large datasets and building data pipelines.</li><li>
Experience with LLMs and generative AI: prompt engineering, fine-tuning, embeddings, RAG systems, or agent frameworks. You understand both the capabilities and limitations.</li><li>
Ability to communicate technical concepts to non-technical stakeholders and work effectively with cross-functional teams.</li><li>
Bachelor's degree in Computer Science, Engineering, Mathematics, Physics, or related quantitative field (or equivalent practical experience).</li><li>
Willingness to travel approximately 30% to client sites as needed.</li></ul><div></div><div>
Preferred Qualifications</div><ul><li>
Experience in Financial Services, Manufacturing, or Energy &amp; Utilities industries.</li><li>
Background in forecasting, optimization, or financial modeling applications.</li><li>
Experience with deep learning frameworks such as PyTorch, Tensorflow, fastai, DeepSpeed, etc.</li><li>
Experience with MLOps tools such as MLflow and Weights &amp; Biases</li><li>
Contributions to open-source projects or familiarity with open-source ML tools and frameworks.</li><li>
Experience building agentic AI systems using Agent Framework (or predecessors), LangChain, LangGraph, CrewAI, or similar frameworks.</li><li>
Cloud certifications (Azure AI Engineer, AWS ML Specialty, or Databricks ML Associate).</li><li>
Consulting experience or demonstrated ability to work across multiple domains and adapt quickly to new problem spaces.</li><li>
Master's degree or PhD in a quantitative field.</li></ul><div></div><div>
Why Huron</div><div>
Variety that accelerates your growth. In consulting, you'll work across industries and problem types that would take a decade to encounter at a single company. Our Commercial segment spans Financial Services, Manufacturing, Energy &amp; Utilities, and more&mdash;each engagement is a new domain to master and a new system to ship.</div><div>
Impact you can measure. Our clients are Fortune 500 companies making significant investments in AI. The models you build will inform real decisions&mdash;production schedules, pricing strategies, risk assessments, capital allocation. You'll see your work drive outcomes.</div><div>
A team that builds. Huron's Data Science &amp; Machine Learning team is a close-knit group of practitioners, not just advisors. We write code, train models, and deploy systems. You'll work alongside engineers and data scientists who understand the craft and push each other to improve.</div><div>
Investment in your development. We provide resources for continuous learning, conference attendance, and certification. As our DSML practice grows, there's significant opportunity to take on technical leadership and shape our capabilities.</div><div></div><div>
Position Level</div>
Associate<div></div><div>
Country</div>
United States of America</div>

Machine Learning Engineer (Associate)

<div><div>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.<br>
<br>
Join our team as the expert you are now and create your future.</div><div></div>
The multi-faceted role you&rsquo;ve been looking for&hellip; Managers play a vibrant, integral role at Huron. Their invaluable knowledge reflects in the projects they manage and the teams they lead. Known for being politically savvy, they build long-standing relationships with clients, while collaborating with colleagues to solve their most important challenges. They plan, shape and deliver technology solutions that deliver results and seamlessly align with client goals, visions and missions. Remarkably versatile, our Managers also spend significant time mentoring junior staff on the engagement team&mdash;where they tirelessly share expertise as well as feedback and encouragement. This benefits Huron profoundly as it promotes a culture of respect, unity, collaboration and personal achievement.<br>
<br>
Our environment inspires and rewards growth&hellip; As a Manager, you have the unique ability to specialize in certain areas of enterprise software products that showcase and employ your areas of expertise while pursuing your &ldquo;career vision&rdquo;. Huron is big enough to offer the opportunity and exposure you need for your career growth&mdash;but small enough to give you individual attention for your professional development. Every Manager adds to who we are as an organization&mdash;and the more you evolve, the more we do. An exciting career experience awaits you where you&rsquo;ll be challenged to discover your true potential: It&rsquo;s analytically rigorous&hellip; it&rsquo;s practical&hellip; it&rsquo;s entrepreneurial&hellip; it&rsquo;s intellectually stimulating&mdash;and most definitely&mdash;it&rsquo;s career-defining. It&rsquo;s the Huron way.<br>
<br>
We see what&rsquo;s possible in you and help you achieve it.<div></div><div>
Qualifications:</div><ul><li>
Bachelor&rsquo;s or Master&rsquo;s degree in a field related to this position or equivalent work experience</li><li>
5-7 years of related experience with ERP cloud implementations in a consulting role</li><li>
3+ years of experience leading Oracle Cloud implementations in one of the following areas: Oracle HCM ORC &ndash; Recruiting or Talent modules</li><li>
End-to-end project implementation experience in one or more of the following areas: Cloud ERP, EPM, CRM or Data Management solutions. Oracle HCM Recruiting or Talent module functional lead experience is a must</li><li>
Experience as a functional application specialist</li><li>
Excellent communication skills &ndash; oral and written &ndash; and the interpersonal skills needed to quickly establish relationships of trust and collaboration</li><li>
Experience with and ability to develop and grow others through effective coaching and leadership</li><li>
Ability to provide industry insights and identify opportunities for value creation based on deep understanding of client (internal or external) challenges</li><li>
Proven ability to contribute on multiple projects of differing scale and duration</li><li>
Willingness to travel up to 50% as needed to work with client or other internal project teams</li><li>
Living location can be anywhere within the contiguous 48 states and near a major airport</li></ul><div>
The estimated base salary for this job is $145,000 - $170,000. The range represents a good faith estimate of the range that Huron reasonably expects to pay for this job at the time of the job posting. The actual salary paid to an individual will vary based on multiple factors, including but not limited to specific skills or certifications, years of experience, market changes, and required travel. This job is also eligible to participate in Huron&rsquo;s annual incentive compensation program, which reflects Huron&rsquo;s pay for performance philosophy. Inclusive of annual incentive compensation opportunity, the total estimated compensation range for this job is $166,750- $212,500. The job is also eligible to participate in Huron&rsquo;s benefit plans which include medical, dental and vision coverage and other wellness programs. The salary range information provided is in accordance with applicable state and local laws regarding salary transparency that are currently in effect and may be implemented in the future.</div><div></div><div>
Position Level</div>
Manager<div></div><div>
Country</div>
United States of America</div>

Digital Consulting Manager - Oracle HCM

<div><div>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.<br>
<br>
Join our team as the expert you are now and create your future.</div><div></div>
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 &amp; 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 &amp; Utilities, and other commercial industries.<br>
<br>
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&mdash;sharing expertise, feedback, and encouragement. This promotes a culture of respect, unity, collaboration, and personal achievement.<br>
<br>
This isn't a reporting role or a dashboard factory&mdash;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.<br>
<br>
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&mdash;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.<div></div><div>
What You'll Do</div><ul><li>
Lead and mentor junior data scientists and analysts&mdash;provide technical guidance, review analytical approaches and code, and support professional development. Foster a culture of intellectual curiosity, rigorous methodology, and clear communication within the team.</li><li>
Manage complex multi-workstream analytics projects&mdash;oversee project planning, resource allocation, and delivery timelines. Ensure analyses meet quality standards and client expectations while maintaining methodological rigor.</li><li>
Design and execute end-to-end data science workflows&mdash;from problem framing and hypothesis development through exploratory analysis, modeling, validation, and insight delivery. Own the analytical approach and ensure conclusions are defensible.</li><li>
Lead development of both traditional statistical and modern AI-powered analyses&mdash;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.</li><li>
Build predictive and prescriptive models that drive business decisions&mdash;customer segmentation, churn prediction, demand forecasting, pricing optimization, risk scoring, and operational efficiency analysis for commercial enterprises.</li><li>
Translate complex analytical findings into actionable insights&mdash;create compelling data narratives, develop executive-ready presentations, and communicate technical results to non-technical stakeholders in ways that drive decisions.</li><li>
Serve as a trusted advisor to clients&mdash;build long-standing partnerships, deeply understand business problems, formulate the right analytical questions, and deliver insights that create measurable value.</li><li>
Contribute to practice development&mdash;participate in business development activities, develop reusable analytical frameworks and methodologies, and help shape the technical direction of Huron's DSML capabilities.</li></ul><div></div><div>
Required Qualifications</div><ul><li>
5+ years of hands-on experience conducting data science and advanced analytics&mdash;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.</li><li>
Experience leading and developing technical teams&mdash;including coaching, mentorship, methodology review, and performance management. Demonstrated ability to build high-performing teams and develop junior talent.</li><li>
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.</li><li>
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.</li><li>
Experience with deep learning and modern neural architectures&mdash;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.</li><li>
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.</li><li>
Exceptional communication and data storytelling skills&mdash;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.</li><li>
Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, or related quantitative field (or equivalent practical experience).</li><li>
Willingness to travel approximately 30% to client sites as needed.</li></ul><div></div><div>
Preferred Qualifications</div><ul><li>
Experience in Financial Services, Manufacturing, or Energy &amp; Utilities industries.</li><li>
Background in experimental design, A/B testing, and causal inference methodologies&mdash;including propensity score matching, difference-in-differences, or instrumental variables.</li><li>
Hands-on experience with deep learning frameworks (PyTorch, TensorFlow) and neural architectures&mdash;including transformers, attention mechanisms, and fine-tuning pretrained models for NLP, time-series, or tabular data applications.</li><li>
Experience building AI-assisted analytical workflows&mdash;leveraging foundation model APIs, vector databases, and retrieval systems to accelerate insight extraction from unstructured data.</li><li>
Experience with Bayesian methods, probabilistic programming (PyMC, NumPyro, etc.), or uncertainty quantification in business contexts.</li><li>
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.</li><li>
Experience with time-series analysis, forecasting methods (ARIMA, Prophet, neural forecasting), and demand planning applications.</li><li>
Cloud certifications (Azure Data Scientist, Databricks ML Associate, AWS ML Specialty).</li><li>
Consulting experience or demonstrated ability to work across multiple domains and adapt quickly to new problem spaces.</li><li>
Master's degree or PhD in Statistics, Applied Mathematics, Economics, or related quantitative field.</li></ul><div></div><div>
Why Huron</div><div>
Variety that accelerates your growth. In consulting, you'll work across industries and analytical challenges that would take a decade to encounter at a single company. Our Commercial segment spans Financial Services, Manufacturing, Energy &amp; Utilities, and more&mdash;each engagement is a new domain to master and a new problem to crack.</div><div>
Impact you can measure. Our clients are Fortune 500 companies making significant investments in analytics and AI. The insights you generate will inform real decisions&mdash;pricing strategies, customer segmentation, operational improvements, strategic investments. You'll see your analysis drive outcomes.</div><div>
A team that thinks deeply. Huron's Data Science &amp; Machine Learning team is a close-knit group of practitioners, not just advisors. We develop hypotheses, analyze data, and deliver insights that hold up to scrutiny. You'll work alongside data scientists and engineers who care about getting the answer right and telling the story clearly.</div><div>
Investment in your development. We provide resources for continuous learning, conference attendance, and certification. As our DSML practice grows, there's significant opportunity to take on technical leadership, shape our capabilities, and advance to senior leadership roles.</div><div></div><div>
Position Level</div>
Manager<div></div><div>
Country</div>
United States of America</div>

Data Scientist (Manager)

<div><div>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.<br>
<br>
Join our team as the expert you are now and create your future.</div><div></div>
Huron is a global consultancy that collaborates with clients to drive strategic growth, ignite innovation, and navigate constant change. We're seeking a Data Scientist to join the Data Science &amp; Machine Learning team in our Commercial Digital practice, where you'll conduct advanced analytics and build predictive models that transform how Fortune 500 companies make decisions across Financial Services, Manufacturing, Energy &amp; Utilities, and other commercial industries.<br>
<br>
This isn't a reporting role or a dashboard factory&mdash;you'll own the full analytics lifecycle from hypothesis formulation through insight delivery. You'll work on problems that matter: experimental designs that validate business strategies, predictive models that surface hidden patterns in complex data, and analytical workflows 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.<br>
<br>
The variety is real. In your first year, you might conduct customer segmentation and lifetime value analysis for a financial services firm, design and analyze a pricing experiment for a global manufacturer, and build an anomaly detection model for a utility company's operational data. If you thrive on rigorous analysis, clear communication of complex findings, and rapid iteration, this role is for you.<div></div><div>
What You'll Do</div><ul><li>
Design and execute end-to-end data science workflows&mdash;from problem framing and hypothesis development through exploratory analysis, modeling, validation, and insight delivery. Own the analytical approach and ensure conclusions are defensible.</li><li>
Develop both traditional statistical and modern AI-powered analyses&mdash;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.</li><li>
Build predictive and prescriptive models that drive business decisions&mdash;customer segmentation, churn prediction, demand forecasting, pricing optimization, risk scoring, and operational efficiency analysis for commercial enterprises.</li><li>
Rapidly build interactive data stories and applications&mdash;deliver insights through compelling visualizations and user-friendly interfaces that stakeholders can explore.</li><li>
Translate complex analytical findings into actionable insights&mdash;create compelling data narratives, develop presentation-ready deliverables, and communicate technical results to non-technical stakeholders in ways that drive decisions.</li><li>
Collaborate directly with clients and senior team members&mdash;understand business problems, formulate the right analytical questions, and contribute to insights that create measurable value.</li></ul><div></div><div>
Required Qualifications</div><ul><li>
2+ years of hands-on experience conducting data science and advanced analytics&mdash;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.</li><li>
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.</li><li>
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.</li><li>
Experience with deep learning and modern neural architectures&mdash;understanding of transformer models, embeddings, and how to leverage foundation models for analytical tasks. You know when ML approaches add value over classical methods.</li><li>
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.</li><li>
Strong visualization and rapid data application development skills&mdash;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.</li><li>
Ability to communicate technical concepts to non-technical stakeholders and work effectively with cross-functional teams. Strong data storytelling skills are essential.</li><li>
Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, or related quantitative field (or equivalent practical experience).</li><li>
Willingness to travel approximately 30% to client sites as needed.</li></ul><div></div><div>
Preferred Qualifications</div><ul><li>
Experience in Financial Services, Manufacturing, or Energy &amp; Utilities industries.</li><li>
Background in experimental design, A/B testing, and causal inference methodologies&mdash;including propensity score matching, difference-in-differences, or instrumental variables.</li><li>
Hands-on experience with deep learning frameworks (PyTorch, TensorFlow) and neural architectures&mdash;including transformers, attention mechanisms, and fine-tuning pretrained models for NLP, time-series, or tabular data applications.</li><li>
Experience building AI-assisted analytical workflows&mdash;leveraging foundation model APIs, vector databases, and retrieval systems to accelerate insight extraction from unstructured data.</li><li>
Experience with Bayesian methods, probabilistic programming (PyMC, NumPyro), or uncertainty quantification in business contexts.</li><li>
Experience with time-series analysis, forecasting methods (ARIMA, Prophet, neural forecasting), and demand planning applications.</li><li>
Cloud certifications (Azure Data Scientist, Databricks ML Associate, AWS ML Specialty).</li><li>
Consulting experience or demonstrated ability to work across multiple domains and adapt quickly to new problem spaces.</li><li>
Master's degree or PhD in Statistics, Applied Mathematics, Economics, or related quantitative field.</li></ul><div></div><div>
Why Huron</div><div>
Variety that accelerates your growth. In consulting, you'll work across industries and analytical challenges that would take a decade to encounter at a single company. Our Commercial segment spans Financial Services, Manufacturing, Energy &amp; Utilities, and more&mdash;each engagement is a new domain to master and a new problem to crack.</div><div>
Impact you can measure. Our clients are Fortune 500 companies making significant investments in analytics and AI. The insights you generate will inform real decisions&mdash;pricing strategies, customer segmentation, operational improvements, strategic investments. You'll see your analysis drive outcomes.</div><div>
A team that thinks deeply. Huron's Data Science &amp; Machine Learning team is a close-knit group of practitioners, not just advisors. We develop hypotheses, analyze data, and deliver insights that hold up to scrutiny. You'll work alongside data scientists and engineers who care about getting the answer right and telling the story clearly.</div><div>
Investment in your development. We provide resources for continuous learning, conference attendance, and certification. As our DSML practice grows, there's significant opportunity to take on technical leadership, shape our capabilities, and advance to senior roles.</div><div></div><div>
Position Level</div>
Associate<div></div><div>
Country</div>
United States of America</div>

Data Scientist (Associate)

<div><div>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.<br>
<br>
Join our team as the expert you are now and create your future.</div><div></div>
Huron is a global consultancy that collaborates with clients to drive strategic growth, ignite innovation, and navigate constant change. We're seeking a Data Engineer to join the Data Science &amp; Machine Learning team in our Commercial Digital practice, where you'll design, build, and optimize the data infrastructure that powers intelligent systems across Financial Services, Manufacturing, Energy &amp; Utilities, and other commercial industries.<br>
<br>
This isn't a maintenance role or a ticket queue&mdash;you'll own the full data lifecycle from source integration through analytics-ready delivery. You'll build pipelines that matter: real-time data architectures that feed mission-critical ML models, transformation layers that turn messy enterprise data into trusted datasets, and orchestration systems that ensure reliability at scale. Our clients are Fortune 500 companies looking for partners who can engineer solutions, not just write SQL.<br>
<br>
The variety is real. In your first year, you might architect a lakehouse solution for a global manufacturer's IoT data, build a real-time streaming pipeline for a financial services firm's trading analytics, and design a data mesh implementation for a utility company's distribution systems. If you thrive on solving complex data challenges and shipping production systems that ML teams and analysts depend on, this role is for you<div></div><div>
What You'll Do</div><ul><li>
Design and build end-to-end data pipelines (batch and streaming)&mdash;from source extraction and ingestion through transformation, quality validation, and delivery. You own the data infrastructure, not just a piece of it.</li><li>
Develop modern data transformation layers using dbt, implementing modular SQL models, testing frameworks, documentation, and CI/CD practices that ensure data quality and maintainability.</li><li>
Build and orchestrate workflows using Microsoft Fabric, Apache Airflow, Dagster, Databricks Workflows, or similar tools to automate complex data processing at scale.</li><li>
Architect lakehouse solutions using open table formats (Delta Lake, Apache Iceberg) on Microsoft Fabric, Snowflake, and Databricks&mdash;designing schemas, optimizing performance, and implementing governance frameworks.</li><li>
Ensure data quality and observability&mdash;implementing testing frameworks (dbt tests, Great Expectations), monitoring, alerting, and lineage tracking that maintain trust in data assets.</li><li>
Collaborate directly with clients to understand business requirements, translate data needs into technical solutions, and communicate architecture decisions to both technical and executive audiences.</li></ul><div></div><div>
Required Qualifications</div><ul><li>
2+ years of hands-on experience building and deploying data pipelines in production&mdash;not just ad-hoc queries and exports. You've built ETL/ELT systems that run reliably and scale.</li><li>
Strong SQL and Python programming skills with experience in PySpark for distributed data processing. SQL for analytics and data modeling; Python/PySpark for pipeline development and large-scale transformations.</li><li>
Experience building data pipelines that serve AI/ML systems, including feature engineering workflows, vector embeddings for retrieval-augmented generation (RAG), and data quality frameworks that ensure model reproducibility. Familiarity with emerging agent integration standards such as MCP (Model Context Protocol) and A2A (Agent-to-Agent), and the ability to design data services and APIs that can be discovered and consumed by autonomous AI agents.</li><li>
Experience with modern data transformation tools, particularly dbt (data build tool). You understand modular SQL development, testing, and documentation practices.</li><li>
Experience with cloud data platforms and lakehouse architectures&mdash;Snowflake, Databricks, and familiarity with open table formats (Delta Lake, Apache Iceberg). We're platform-flexible but Microsoft-preferred.</li><li>
Familiarity with workflow orchestration tools such as Apache Airflow, Dagster, Prefect, or Microsoft Data Factory. You understand DAGs, scheduling, and dependency management.</li><li>
Solid understanding of data modeling concepts: dimensional modeling, data vault, normalization/denormalization, and knowing when different approaches are appropriate.</li><li>
Ability to communicate technical concepts to non-technical stakeholders and work effectively with cross-functional teams including data scientists, analysts, and business users.</li><li>
Bachelor's degree in Computer Science, Engineering, Mathematics, or related technical field (or equivalent practical experience).</li><li>
Willingness to travel approximately 30% to client sites as needed.</li></ul><div></div><div>
Preferred Qualifications</div><ul><li>
Experience in Financial Services, Manufacturing, or Energy &amp; Utilities industries.</li><li>
Background in building data infrastructure for ML/AI systems&mdash;feature stores (Feast, Databricks Feature Store), training data pipelines, vector databases for RAG/LLM workloads, or model serving architectures.</li><li>
Experience with real-time and streaming data architectures using Kafka, Spark Streaming, Flink, or Azure Event Hubs, including CDC patterns for data synchronization.</li><li>
Familiarity with MCP (Model Context Protocol) or similar standards for AI system data integration.</li><li>
Experience with data quality and observability frameworks such as Great Expectations, Soda, Monte Carlo, or dbt tests.</li><li>
Experience with high-performance Python data tools such as Polars or DuckDB for efficient data processing.</li><li>
Knowledge of data governance, cataloging, and lineage tools (Unity Catalog, Purview, Alation, or similar).</li><li>
Familiarity with DataOps and CI/CD practices for data pipelines&mdash;version control, automated testing, and deployment automation.</li><li>
Cloud certifications (Snowflake SnowPro, Databricks Data Engineer, Azure Data Engineer, or AWS Data Analytics).</li><li>
Consulting experience or demonstrated ability to work across multiple domains and adapt quickly to new problem spaces.</li><li>
Contributions to open-source data engineering projects or active participation in the dbt/data community.</li><li>
Master's degree in a technical field.</li></ul><div></div><div>
Why Huron</div><div>
Variety that accelerates your growth. In consulting, you'll work across industries and data architectures that would take a decade to encounter at a single company. Our Commercial segment spans Financial Services, Manufacturing, Energy &amp; Utilities, and more&mdash;each engagement is a new data ecosystem to master and a new platform to ship.</div><div>
Impact you can measure. Our clients are Fortune 500 companies making significant investments in data infrastructure. The pipelines you build will power real decisions&mdash;the ML models that drive production schedules, the dashboards that inform pricing strategies, the data products that enable self-service analytics. You'll see your work become the foundation others build on.</div><div>
A team that builds. Huron's Data Science &amp; Machine Learning team is a close-knit group of practitioners, not just advisors. We write code, build pipelines, and deploy platforms. You'll work alongside engineers and data scientists who understand the craft and push each other to improve.</div><div>
Investment in your development. We provide resources for continuous learning, conference attendance, and certification. As our DSML practice grows, there's significant opportunity to take on technical leadership and shape our data engineering capabilities.</div><div></div><div>
Position Level</div>
Associate<div></div><div>
Country</div>
United States of America</div>

Data Engineer (Associate)

Join Huron Consulting Group and explore 8   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.