Data Scientist – QuantumBlack, AI by McKinsey needed at McKinsey & Company

Role responsibilities

• Work on complex and extremely varied data sets from some of the world’s largest organisations to solve real world problems
• Develop data science products and solutions for clients as well as for our data science team
• Write highly optimized code to advance our internal Data Science Toolbox
• Work in a multi-disciplinary environment with specialists in machine learning, engineering and design
• Focus on modelling by working alongside the Data Engineering team
• Add real-world impact to your academic expertise, as you are encouraged to write papers and present at meetings and conferences should you wish
• Take part in R&D (video: R&D at QuantumBlack); attend conferences such as NIPS and ICML as well as data science retrospectives where you will have the opportunity to share and learn from your co-workers
• Work in one of the most advanced data science teams globally 

What you’ll learn

• How successful projections on real world problems across a variety of industries are completed through referencing past deliveries of end to end machine learning pipelines
• Build products alongside the Core engineering team and evolve the engineering process to scale with data, handling complex problems and advanced client situations
• Best practices in software development and productionise machine learning by working with our Machine Learning Engineering teams which optimise code for model development and scale it
• Work with our UX and Visual Design teams to interpret your complex models into stunning and user-focused visualisations
• Using new technologies and problem-solving skills in a multicultural and creative environment

Your qualifications and skills

• Bachelor’s, masters or PhD level in a discipline such as: computer science, machine learning, applied statistics, mathematics, engineering or artificial intelligence
• Up to 3 years of professional experience in applying machine learning and data mining techniques to real problems with copious amounts of data
• Programming experience (focus on machine learning): R and/or Python (must), SPSS, SAS, Ruby, Hadoop (valued)
• Data treatment/data mining, e.g. SQL, AWK, Access, Spark, Excel (highly valued)
• Statistical knowledge is a plus
• Demonstrated aptitude for analytics
• Proven record of leadership in a work setting and/or through extracurricular activities
• Ability to prototype statistical analysis and modeling algorithms and apply these algorithms for data driven solutions to problems in new domains
• Ability to independently own and drive model development, balancing demands and deadlines
• Demonstrated aptitude for analytics
• Good presentation and communication skills, with the ability to explain complex analytical concepts to people from other fields 
• Willingness to travel