Qualifications

Bachelor's degree; Master's degree is a plus

7+ years of experience in the Oil & Gas sector

Hands-on experience working with advanced analytics and data science teams, with a working knowledge of programming languages such as R and Python

Knowledge in advanced analytics, including knowing how to “translate” complex data into easily digestible action items within a business context to external and internal audiences

Demonstrable passion for both analytics and performance improvement in the Oil & Gas sector

Understanding of what’s driving the O&G; industry, with an unparalleled understanding of - and depth of knowledge in - technology, analytics, and the use of data

Strong intrinsic problem solving skills, the ability to structure and solve problems and conduct and interpret analysis independently, with demonstrated analytic and quantitative skills

Unique knowledge, including the ability to apply data and analytics to improve reliability, e.g., by refining maintenance strategies, designing first response, or predicting failures

Ability to prepare and lead productive problem team meetings and problem solving discussions through strong presentation and facilitation skills

Strong knowledge of the competitive landscape, and how to position McKinsey’s capabilities in a way that resonates with clients

Demonstrable evidence in running internal and client meetings independently

Willingness to travel up to four days per week, with international travel as required

Who You'll Work With

You'll be based in either Amsterdam, Dubai, Munich, Vienna or Oslo and will work within our Petroleum Asset eXcellence (PAX ) team, a part of McKinsey’s global Oil & Gas practice. Petroleum Asset eXcellence is a part of McKinsey’s New Ventures.

PAX helps clients unlock the full value of their Oil & Gas assets in a sustainable way using a combination of deep industry expertise and reliable, tested solutions. Our Oil & Gas practice serves clients across the entire Oil & Gas value chain, helping them manage risk and uncertainty, strengthening their organizations and improving performance.

McKinsey New Ventures fosters innovation driven by analytics, design thinking, mobile and social by developing new products/services and integrating them into our client work. It is helping to shift our model toward asset-based consulting and is a foundation for –and expands our investment in –our entrepreneurial culture. Through innovative software as a service solutions, strategic acquisitions, and a vibrant ecosystem of alliances, we are redefining what it means to work with McKinsey.

As one of the fastest-growing parts of our firm, New Ventures has more than 1,500 dedicated professionals (including more than 800 analysts and data scientists) and we’re hiring more mathematicians, data scientists, designers, software engineers, product managers, client development managers and general managers

What You'll Do

You will be part of a team of exceptional advisory professionals with similarly deep industry experience.

By harnessing the power of advanced analytics within our Oil & Gas client organizations, you will help our clients adapt their operations in response to the continuing growth of advanced technologies, including digital manufacturing. You will generate excitement among McKinsey colleagues and clients about the potential and value of data and analytics. You will be a thought leader, introducing industry-changing insights in digital technologies in O&G; to McKinsey colleagues and clients.

You will work closely with data scientists to communicate complex data related requirements between multiple stakeholders, often taking responsibility for a workstream, usually with a strong analytics component. You will design and develop analytics tools and capabilities as part of usual client service and support the implementation of organisational and operational change, working effectively alongside colleagues to develop ambitious change programmes.

You will facilitate working sessions and meetings with O&G; executives, managers, engineers and staff to help them make plans to capture improvement opportunities whilst also contributing to and leading the development of content knowledge and analytics capabilities and solutions.