Description

Equity Methods seeks a results-focused, growth-oriented professional to support and drive client
engagements serving the chief human resources officers and compensation executives at Fortune 500 companies and beyond. Our HR advisory practice offers you the ability to apply core economics and quantitative science principles in a rigorous yet applied capacity. Our work directly impacts the C-suite at client firms on topics in workforce analytics such as pay equity, talent mobility analytics, workforce planning, and incentive design.

You will lead complex client engagements and be responsible for delivering high-impact solutions that leverage your background in economics, in addition to supervising associates on the team. This custom pathway into a senior consulting role is designed for graduate degree holders (Masters or PhD) in Economics, Finance, Accounting, Statistics, Industrial/Organizational Psychology, or other applied quantitative sciences. The role will blend data analysis and modeling, statistics, consulting, and AI to help clients optimize their workforce. This client-facing role will lead engagements and collaborate with the team to build predictive models, drive pay equity studies, and perform other talent analytics. The skills needed for this role include:

• Fluent in classical and applied econometrics
• Ability to build repeatable, well-documented models that comply with industry-accepted frameworks and regulatory standards, as applicable
• Ability to visualize complex technical results clearly for non-technical audiences
• Ability to translate analysis results into plain-English for actionable insights and recommendations for HR and C-suite stakeholders
• Interest in contributing to thought leadership that advance EM's services

If you enjoy problem-solving, are interested in a client-facing applied role, and enjoy geeking out with technical models, then we would like to meet you and discuss this exciting role.

The Role in a Nutshell

• Prior professional services experience is not required, and neither is compensation or workforce analytics experience. Although every day will be different, Economists in this role will:
• Complete initial training in compensation and workforce analytics projects, ranging from broad-based compensation issues to incentive design to statistical pay equity analysis.
• Lead projects and deliver guidance on statistical matters in pay equity, talent mobility, workforce planning, and other workforce analytics-related projects for clients across industries and company sizes.
• Contribute to compensation strategy projects, in which we are engaged by public and private companies to recommend new incentive programs that support critical business objectives.
• Capture recommendations and analytics for external and internal audiences in superbly structured and clear PowerPoint presentations and Excel worksheets.
• Perform research using clients' 10-K and proxy statements to form viewpoints on market compensation practices, including pay levels, incentive structures, corporate governance, disclosure, and equity dilution.
• Analyze broad-based compensation benchmarking survey data to recommend employee pay levels in light of industry and peer practices.
• Monitor and interpret the regulatory landscape for pay equity and workforce analytics (e.g., EUPTD, OFCCP, EEOC, state and international pay transparency requirements) to keep methodologies current and defensible.

The Economist role is not expected to be a back-office technical role. Whereas candidates with prior work experience in professional services can segue quickly into formal client management roles, we expect all candidates to learn the ropes of managing consulting projects and transition formally into this segment of our career progression framework.

Competencies of the Successful Candidate

• Flexes and adapts to changing circumstances. We constantly face shifting priorities, challenging projects, and tight turnarounds. We try to bend to deliver to our clients during their greatest moments of need, which requires flexibility.
• Rigorous technical background. Our work is customized and rigorous, which may include the statistical modeling underpinning a pay equity project or clarity of reasoning on incentive design projects.
• Exceptional written and verbal communication. Great client work product consists of rigorous analysis and highly polished materials, and we believe you can't have one without the other. Attention to detail, strong writing skills, and clear communication are musts.
• Thrives on feedback. Our team is focused forward on improvement and creating excellence, never backward on blame, and we seek out feedback to become better versions of ourselves.
• Thrives in an ambiguity-rich environment. As a result of pushing new boundaries, we often find ourselves outside of our individual and collective comfort zones. This spells ambiguity, the need for research, and a desire to experiment iteratively toward the right answer-which some people love and others do not.
• Works autonomously but is comfortable in groups. Much of the in-the-weeds work of our engagements requires our consultants to perform excellent analysis individually before sharing, testing, and iterating with the team. This requires doing great work with little to no oversight as well as comfort considering, discussing, and implementing others' viewpoints.
• Excels at data analysis and visualization. Many engagements involve some sort of modeling and analysis. We are known for drawing rich insights from data and communicating it in a plain-English, visualization-heavy way to our clients.

Qualifications & Requirements

• PhD or Masters in Statistics, Economics, Finance, Accounting, Industrial/Organizational Psychology, or another quantitative social science related field.
• Prior experience in compensation, pay equity, or workforce analytics is not required.
• Prior work experience in consulting or professional services role is not required, but having this background is a plus.
• Strong Excel skills and the ability to design robust, insight-rich models.
• Coding experience in SAS, Python, R, or STATA
• Strong detail- and accuracy-orientation. Successful candidate must demonstrate attention to detail with regard to internal and external communication, creating and reviewing deliverables, and performing modeling analyses.
• Ability and willingness to think critically and solve "out-of-the-box" problems independently.
• Background check required.