The Commercial Policy & Analytics (CP&A) team provides a one-stop shop for all commercial activities, partnering with front-line teams to support revenue growth and fully monetize the value GLG delivers to its clients while consistently evolving and optimizing GLG’s pricing methodology.
We are seeking an Associate to join the team in New York. You will employ your analytical toolkit, problem-solving skills, and commercial acumen to improve GLG’s profitability and continually evolve our pricing strategy.

Specific responsibilities include (but are not limited to):

• Execute the current pricing and commercial strategy

o Drawing on your data analysis skills and your acquired contextual knowledge of our business and its key drivers, you will partner with Sales, Client Solutions, and Business Unit Management to provide timely and creative pricing recommendations and ad hoc scenario analysis

• Contribute to our approach to pricing and commercial strategy

o Using historical data, real-time feedback from our client-facing teams, competitive intelligence, and your own analytical insights, you will continually contribute to our definition of success for pricing, the factors that drive it, the different strategies for achieving it, and how we incentivize it

• Evolve commercial reporting and data architecture (in collaboration with our Business Intelligence / Data Engineering teams)

o Own and refine existing reporting and relevant data production processes

o Identify which data needs to be captured, how it needs to be stored and accessed, and how it should be visualized and consumed by different levels of stakeholders

• Contribute to technical tools that enable internal business automation

o Provide ideas on ways to improve tooling that codifies commercial policy and empowers front-line teams (e.g., CRM, CPQ, self-service scenario analysis tools)
o Work closely with Enterprise Technology teams to provide business requirements for the development of efficient tools

An ideal candidate will have the following:

• BA/BS from a leading undergraduate institution, preferably with a major in a quantitative field (e.g., Economics, Math, Engineering, Finance, Statistics, Computer Science)
• 1-3 years of professional experience in either:

o A highly quantitative problem-solving environment like investment banking, consulting, FP&A, corporate strategy, and/or sales strategy

o A business analyst role with heavy emphasis on data cleaning, transformation, modeling, and visualization

• Fluency in Excel, SQL, and one or more of the common data science languages (e.g., Python, R); understanding of statistical analysis (e.g., hypothesis testing, predictive models) a plus
• Understanding of basic profitability metrics
• Experience within a market-facing or commercial business partnering role preferred (because data models only take you so far when there are people in the equation)
• Ability to synthesize numerous data-backed conclusions into a succinct story that clearly identifies the main drivers and recommended action steps
• Comfort with, and even passion for, having the data prove your hypotheses wrong
• Self-starter mentality who thrives on operating with autonomy to derive insights, suggest paths of action, and drive projects to completion with minimal guidance
• Deep level of attention to detail
• Ability to manage multiple stakeholder relationships, using your emotional intelligence and persuasion skills rather than direct authority to influence day-to-day pricing decision

Specific responsibilities include (but are not limited to):

• Execute the current pricing and commercial strateg

o A business analyst role with heavy emphasis on data cleaning, transformation, modeling, and visualization

• Fluency in Excel, SQL, and one or more of the common data science languages (e.g., Python, R); understanding of statistical analysis (e.g., hypothesis testing, predictive models) a plus
• Understanding of basic profitability metrics
• Experience within a market-facing or commercial business partnering role preferred (because data models only take you so far when there are people in the equation)
• Ability to synthesize numerous data-backed conclusions into a succinct story that clearly identifies the main drivers and recommended action steps
• Comfort with, and even passion for, having the data prove your hypotheses wrong
• Self-starter mentality who thrives on operating with autonomy to derive insights, suggest paths of action, and drive projects to completion with minimal guidance
• Deep level of attention to detail
• Ability to manage multiple stakeholder relationships, using your emotional intelligence and persuasion skills rather than direct authority to influence day-to-day pricing decisio