Assignment description 

Our client is looking for an experienced Senior Data Scientist to join the Personlization team. As part of the team, you will study user behaviour, strategic initiatives, product features, and more bringing data and insights into every decision they make. Your work will impact how they think about their users, their ability to identify and satisfy their needs, and build compelling customer support offerings and experiences informed by those needs. You and the rest of the team will be able to directly impact how millions of users are supported around the world. Above all, your work will affect the way the world experiences audio listening.

What you’ll do:

• Co-operate with cross-functional teams of data scientists, user researchers, product managers, designers and engineers who are passionate about their consumer experience across platforms and partners
• Perform analyses on large sets of data to extract impactful insights on user behaviour that will help drive product and design decisions
• Communicate insights and recommendations to stakeholders across the company
• Evaluate of ML models in particular it’s impact on user experience, business metrics and assess how does the model behave in different scenarios
• Develop metrics for experimentation and monitoring of ML models, including running correlation between offline and online evaluation

Who you are:

• You enjoy sharpening questions and developing hypothesis for yourself and can think together with others while clarifying their assumptions and hypothesis
• You care about answering questions and thinking of new questions that can propel our product forward
• You have relevant experience of working as a Data Scientist in a large B2C context
• You have experience of working on large scale experimentation platforms and can analyze large scale AB Tests
• You are conversant with ML evaluation methods
• You have the necessary technical skills such as:
  • Coding skills (for example Python/R)
  • Analytics tools experience (such as Pandas, R, SQL)
  • Statistical competence (such as regression modelling, a/b testing, significance testing etc.)