Data Scientist - Defense and Security

Who you'll work with

You will be based in our Washington, D.C. office as part of our Defense and Security team. You will work with senior members of the US defense and security community on some of their highest priority issues. Typically, you’ll work locally in the Washington, D.C. area in blended teams of 3 – 5 colleagues, each with varying types of expertise (e.g., digital, strategy, operations, analytics).

What you'll do

You will develop and apply data science methods to improve and optimize our clients performance needs. In this role, you will support our client services lead to identify business hypotheses and metrics, and you'll define and drive the analytical scope and method for projects, including formulating and shaping the models. You will communicate complex analytics concepts in a clear and concise manner to business leaders. You will use math, stats, and machine learning to derive key insights across various topics within defense and security. You will write highly optimized code to advance our internal Data Science toolbox, and you'll develop world-class data science products for clients as well as for our data science team. Much of your work will be project-based, and varied. At McKinsey, we help our Defense and Security clients on a broad range of topics requiring data and analytics, including driving Readiness outcomes, optimizing workflows, forecasting supply and demand, increasing financial transparency, reducing supply chain risks, and improving workforce outcomes. At other times, you will take a “product” view and help us turn an MVP into an asset deployable across organizations. You will join a firm that will challenge you and invest heavily in your professional development, building on the strengths you bring to the firm. Data science consultants receive exceptional training as well as frequent coaching and mentoring from colleagues on their teams.

Qualifications

• Bachelor’s degree required in STEM field; Advanced degree strongly preferred
• 3+ years of advanced hands-on data science & analytics experience using Python and R; some exposure to SQL
• TS/SCI clearance with polygraph required
• Knowledge and experience applying common data science methods, including linear models, tree-based models, SVMs, ensemble methods (e.g., random forest), and unsupervised/clustering methods
• Experience with descriptive statistics and exploratory data analysis (EDA)
• Experience in working with large datasets in flat files, relational databases, and distributed systems (Hadoop). Some exposure to AWS, Azure, and/or GCP desirableExperience in visualization tools (e.g., Tableau, Tibco Spotfire, Qlik) is highly desirable
• Passion for applying analytics methods to improve mission and business decisions
• Strong people skills, team orientation, and a professional attitude
• Ability to communicate complex ideas effectively, both verbally and in writing