Data Science Consultant - McKinsey Analytics

Key Skills

Python Programming, PySpark, SQL, Apache Airflow, Databricks, Kedro, AWS, Google Cloud Platform (GCP), Azure, Scala Programming, RDBMS, PostgreSQL, Amazon RedShift, Teradata, Snowflake, NoSQL, Apache Cassandra, Neo4J, Titan, MongoDB

Job Description

Who You'll Work With

You will be based in Paris and will be part of McKinsey Analytics, serving clients from the region.

Given the unprecedented proliferation of data in the world today and our clients’ growing need to understand and capture value from it, McKinsey Analytics is rapidly expanding. Ongoing investments in our people and technology platform, combined with acquisitions of leading-edge firms like QuantumBlack and Risk Dynamics, have made us one of the largest and most esteemed advanced analytics consultancies today. 

Combining state-of-the-art tools and techniques with McKinsey’s 85-plus years of experience, we enable our clients to improve their performance through data and become analytics-driven organizations. Our work across the analytics landscape is driven by experts with a broad range of analysis, coding, modelling, design and system-architecture disciplines. We apply these to achieve measurable and outsize impact on real-world problems such as reducing crime, improving healthcare, optimizing manufacturing and improving customer experiences.

A critical part of McKinsey’s mission is to create an unrivaled environment for exceptional people. We pride ourselves on fostering an atmosphere of ongoing learning and development for those seeking to constantly enhance their capabilities and knowledge. Through efforts like internal grant programs, continuing education, and secondment opportunities, learning and skills-improvement opportunities are endless for our data professionals around the world.

What You'll Do

?You will focus on the development of advanced analytics models to optimize underlying business problems.

In this role, you will work through our clients’ entire data ecosystem to understand what’s available, what’s missing and where to find and collect that information. You will develop, implement and maintain effective programs around all elements of data engineering and modeling with a constant eye toward continuous improvement.

You will apply data science methods to improve and optimize our clients performance needs, capture meaningful insights from data and turn them into competitive advantages. You will help in the creation of statistical models to solve specific operational problems which may include predicting equipment failure to do proactive maintenance for wind turbines, determining how to use machine learning to predict consumer behavior, etc. In solving these problems, you will have access to proprietary feature engineering AI and teams of world-leading experts in your domain. You will be in the room, often with the senior management, working side by side with talented data scientists from leading client organizations both on technical issues and on making the change happen.

Qualifications

• Advanced degree in statistics, mathematics or econometrics, economics, operations research or any related quantitative discipline with strong academic qualifications
• Up to 5 years of post-university deep technical experience in predictive analytics, machine learning, optimization, etc.
• Good knowledge of statistical approaches including advanced machine learning techniques (e.g. data science, support vector machines, neural nets, deep learning, machine learning) and/or optimization
• Fluent in a number of the following technologies: R, Python, Julia, SQL, GMPL or related
• French and English fluency
• Willingness to travel up to 80%