Fellow, Data Science – QuantumBlack

  • Jornada Completa
  • LinkedIn
  • Madrid

QuantumBlack 

Fellow, Data Science – QuantumBlack

Acerca del empleo

Qualifications

  • Bachelor or MSc or PhD level degree in a discipline such as computer science, machine learning, applied statistics, mathematics or engineering.
  • Ability to write clean, maintainable, and robust code in Python
  • Good presentation and communication skills, with the ability to explain complex analytical concepts to people from other fields
  • Methodical yet creative problem solver
  • Experience in applying data science and machine learning methods to real world problems

What You’ll Do

You will work in multi-disciplinary environments harnessing data to provide real-world impact for organisations globally.

You will influence many of the recommendations our clients need to positively change their businesses and enhance performance.

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
  • Add real-world impact to your academic expertise, as you are encouraged to write ‘black’ papers and present at meetings and conferences should you wish
  • Attend conferences such as NIPS and ICML as one global team as well as Data Science retrospectives where you will have the opportunity to share and learn from your co-workers.
  • Work within one of the largest and most advanced data science teams in London, support the Lead Data Scientists to develop data science products

Who You’ll Work With

You will be based in Milan and will work with other data scientists, data engineers, machine learning engineers, designers and project managers on interdisciplinary projects, using maths, stats and machine learning to derive structure and knowledge from raw data across various industry sectors.

Por favor, para apuntarte a este trabajo visita www.linkedin.com.