Senior Data Scientist - Financial Engineering (Remote Eligible - EMEA)

Key Skills

Python Programming, Scala Programming, C++, Java Programming, Machine learning techniques, Data science techniques, SQL, Apache Hadoop, MapReduce, TensorFlow, PyTorch, R Programming

Job Description

We are looking for an experienced senior data scientist for our Financial Engineering organization. Our mission is to build the technical platform that underpins our key company decisions, revenue and royalty calculations, financial performance management and our ability to scale out to new markets and products.

As a data scientist you will be part of a team of experienced data engineers and other data scientists building data pipelines and drawing insights from data for the whole company. Your role will be to drive and deliver world-class data analysis, data science products and machine learning solutions to empower business partners and other engineers to understand and make decisions based on our data.

What you'll do

• Create insights based on huge amount of data using cutting edge data science tools and methodologies
• Build data science and machine learning tools for the Finance organization allowing to rapidly and automatically analyze data and support decision making
• Be responsible for the data science features of products developed by cross functional teams
• Perform internal user research to understand the needs of other Spotify employees
• Rapidly prototype ideas to validate them with real data and real users
• Work on an interdisciplinary team of engineers, data scientists, designers, and product managers
• Collaborate with engineers to productionize your designs

Who you are

• You have 5+ years of experience building data science solutions and working machine learning.
• Degree in data science, computer science, statistics, economics, mathematics, or a similar quantitative field. PhD welcome.
• Solid understanding of algebra, statistics, optimization and machine learning.
• You are experienced in programming in at least one language (Python, R, Matlab, ...) and are comfortable with getting data by yourself (SQL, BigQuery, ..)
• You are experienced using standard machine learning libraries (scikit-learn, keras, ...)
• Strong communication skills and value building strong relationships with colleagues and partners as well as the ability to explain sophisticated topics in straightforward terms.
• You’re a compelling storyteller who can communicate in succinct and inspiring ways to audiences with varied data science experience to influence real world product or feature decisions.
• Comfortable working with distributed teams across multiple offices and timezones.

Where you'll be

• We are a distributed workforce enabling our band members to find a work mode that is best for them!
• Where in the world? For this role, it can be within the EMEA region in which we have a work location
• Prefer an office to work from home instead? Not a problem! We have plenty of options for your working preferences. Find more information about our Work From Anywhere options here.
• Working hours? We operate within the CEST time zone for collaboration

Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.

Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service with a community of more than 345 million users.