You will be based in one of our locations in the Americas or
Europe as part of our finance advanced analytics team.
Finance advanced analytics develops innovative data science and
advanced analytics models for our global finance operation's most
difficult data-driven challenges. The group works on a variety of
business problems from core finance areas, and also supports client
service functions with tailor made models.
You will collaborate with internal clients and a diverse team of
data scientists, data engineers, subject matter experts and
business leaders to shape tools, analyses, dashboards and other
deliverables in a way that maximizes opportunity for impact.
You will work with leaders and members from different groups
within and beyond our finance function to drive use-cases through
all aspects of the data science pipeline.
In this role, you will help these stakeholders identify use
cases from their areas where advanced analytics tools have the
potential to drive additional impact. While developing bespoke
solutions for those business problems, you will collaborate with
colleagues who have specific expertise in each relevant area and
can act as a translator between the data science side and the
business side. These colleagues often are finance specialists, but
may also include subject matter experts from other areas, such as
people analytics, client service and the McKinsey Global
You will work closely with the firm's data and information
technology experts to define data and data structures that enable
current and future finance advanced analytics use cases in the best
possible way. This will include working with data owners and
knowledge experts to procure and understand relevant data sets.
You will build data science models using a variety of
methodologies. Past projects have involved time-series, machine
learning, statistics, optimization, and simulation. You will
analyze and interpret the results and progress of analytical
efforts, delivering clear, well-structured communication to
internal clients and stakeholders using a variety of formats (e.g.
demos, presentations). In addition, you will contribute to the
team's strategic agenda.
- Degree in applied mathematics (e.g. statistics, machine
learning, operations research, etc.); master's degree
- 2+ years of technical experience
- Deep understanding of data science principles and
- Ability to program data science workflows in Python; knowledge
in SQL and R is a plus
- Exceptional analytical and quantitative problem-solving
- Integrity and professionalism in dealing with confidential
- Superior communication and collaboration skills; ability to
communicate crisply and clearly with firm leaders