Senior Workforce Strategy Consultant
$165.5k - $331kMercer Consulting
Marsh is seeking an experienced Senior Workforce Strategy Consultant to join our Workforce and Rewards team . This role combines deep workforce analytics and human capital strategy with practical, responsible use of AI to deliver faster, more powerful, and more actionable insights. You will help clients predict, shape, and optimize workforce outcomes by blending traditional labor economics, I/O psychology, and statistical rigor with modern AI-assisted analytics, model governance, and operationalized data products.
We will count on you to:
- Translate business problems into analytics-driven workforce solutions that combine qualitative research, advanced statistics, and AI-enabled methods (including machine learning and large language models) to uncover workforce dynamics and strategic opportunities.
- Design, build, and operationalize analytic models and data products (e.g., forecasting models, skills taxonomies, retention risk scoring, internal mobility recommendations) that leverage structured data, unstructured text (job descriptions, performance feedback), and third-party labor market signals.
- Lead client engagements as the analytics and AI subject-matter lead: define analytic approaches, present findings, translate insights into prioritized workforce investments, and co-create implementation roadmaps with client stakeholders.
- Drive pay equity, strategic workforce planning, and external labor market analyses using both classical econometrics and AI-enhanced approaches; quantify business impact and ROI for recommended interventions.
- Create and deliver clear, compelling deliverables—interactive dashboards, visualizations, client-ready slide decks, and data stories—using best practices in interpretability and design so technical results are actionable for HR and business leaders.
- Ensure responsible AI use: implement model validation, bias detection and mitigation, explainability techniques, privacy-preserving practices, and documentation consistent with client and regulatory requirements.
- Contribute to Marsh's intellectual capital: create reusable AI-enabled frameworks, client accelerators, proposals, and thought leadership that reflect emerging practice in AI-driven workforce strategy.
What success looks like:
- Clients adopt model-driven workforce decisions (e.g., hiring prioritization, targeted retention programs, reskilling investments) that measurably improve engagement, productivity, or cost-efficiency.
- Analytic products are accurate, explainable, reproducible, and built with operational controls so clients can scale and govern them post-engagement.
What you need to have:
- 8+ years of relevant consulting experience in workforce strategy, HR analytics, labor economics, organizational psychology, or a closely related field.
- Master’s or PhD in economics, I-O psychology, statistics, data science, computer science, labor relations, or another quantitative discipline.
- Demonstrated experience in pay equity analysis, strategic workforce planning, external labor market analysis, or comparable workforce consulting engagements.
- Strong statistical and machine learning skills: regression, causal inference, time series, clustering, and predictive modeling.
- Proficiency in modern data tooling and languages (e.g., Python, R, SQL) and experience with visualization tools (e.g., Tableau).
- Hands-on experience extracting value from large and varied datasets and translating technical outputs into business actions.
- Excellent storytelling, client-facing communication, and project leadership skills.
What sets you apart:
- An AI-native mindset: you can evaluate new tools quickly, integrate them responsibly into client workstreams, and clearly communicate trade-offs (accuracy, speed, explainability, privacy).
- A consultative approach that couples rigorous analytic technique with pragmatic implementation focus—able to move clients from insight to measurable action.
- Comfortable directing analysis end-to-end: from data strategy and ingestion through modeling, validation, visualization, and deployment guidance.
Why join our team:
- We help you be your best through professional development opportunities, interesting work, and supportive leaders.
- We foster a vibrant and inclusive culture where you can work with talented colleagues to create new solutions and have an impact for colleagues, clients, and communities.
- Our scale enables us to provide a range of career opportunities, as well as benefits and rewards to enhance your well-being.
Marsh (NYSE: MRSH) is a global leader in risk, reinsurance and capital, people and investments, and management consulting, advising clients in 130 countries. With annual revenue of over $27 billion and more than 95,000 colleagues, Marsh helps build the confidence to thrive through the power of perspective. For more information, visit marsh.com, or follow us on LinkedIn and X.
Marsh is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age background, disability, ethnic origin, family duties, gender orientation or expression, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, veteran status (including protected veterans), or any other characteristic protected by applicable law. If you have a need that requires accommodation, please let us know by contacting View email address on click.appcast.io. Marsh is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one “anchor day” per week on which their full team will be together in person. The applicable base salary range for this role is $165,500 to $331,000.The base pay offered will be determined on factors such as experience, skills, training, location, certifications, education, and any applicable minimum wage requirements. Decisions will be determined on a case-by-case basis. In addition to the base salary, this position may be eligible for performance-based incentives.
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