EMEA Data Scientist I, Ops

About The Role

The EMEA Data Science Ops team goal is to enable EMEA Ops org to improve their decision-making by using modeling capabilities to make better decisions and to measure the effectiveness of their decisions and actions via experimentation and quasi-experimentation.

Your primary responsibilities will revolve around these two pillars, modeling and experimentation: aligning with business objectives, formulating clear problem statements, and managing data through collection, cleaning, and structuring. You will also conduct analytical explorations, apply experimentation techniques and modeling, and effectively communicate the results.

You will explore opportunities across a range of topics. This includes designing and executing experiments within the Uber marketplace and using ML to improve our personalization models. Additionally, you will work using Causal Inference models for policy evaluation, Optimization models for pricing, or investment challenges, among other tools.

What The Candidate Will Need / Bonus Points

---- What the Candidate Will Do ----

Reporting to the Data Science Manager leading our Data Science Ops team, this person will be responsible for:

• Modeling, including building or validating existing optimization and predictive ML models.
• Experimentation, including designing and executing experiments to test / answer specific business questions, or to support launch and roll out plans of new products or features
• Causal Inference: using inference techniques to evaluate actions and policies, particularly in cases where experimentation is not an option.
• Stakeholder Management; build strong relationships with teams in both central and local operations, to help identify, shape, execute and evaluate business opportunities underpinned by advanced quantitative methods.
  
  

Basic Qualifications

• 2+ years of experience (Bachelor) or 2+ years of experience (Masters) in a data-focused role such as product analytics, business analytics, business operations, or data science
• Postgraduate degree / research experience in STEM subjects
• Strong knowledge in SQL, Python (for Data Science)
• Fundamental knowledge of causal inference, experimentation, and econometrics statistics methods for analytical problems.
• Ability and motivation to learn and quickly apply new quantitative methods and techniques to business contexts.
• Love of data - you just go get the data you need and turn it into an insightful story.
• A well-organized, structured approach to problem-solving
  
  

Preferred Qualifications

• You have Stakeholder mgmt. experience, ideally in a business context
• Strong interpersonal skills with the ability to be an excellent team player and assist colleagues.
• The ability to communicate effectively and to coordinate multiple stakeholders in ambiguous circumstances
• Experience working with one or more of the following expertise fields: Causal ML, Optimization - Operations Research, Machine Learning