We are looking for a Data Scientist to join our fraud product area. Our mission is to accelerate Spotify’s growth with a trusted platform that provides insights and data to our partners. The work we do to detect, prevent, and mitigate unwanted behaviour on our platform is a key component of our ambitious goals.
You will be joining a diverse team of engineers and data scientists that use machine learning, research, state of the art data engineering, and a deep theoretical understanding to solve some of the most advanced and important data-driven problems we face. For example:
- Evolve and scale out our fraud platform
- Research and develop how advanced data science techniques and machine learning can enable and empower our fraud detection capabilities
- Consistently consume and produce massive amounts of data while optimising for speed, accuracy, and quality
- Innovate our data products to create a single coherent platform with sources of truth that serve a plethora of stakeholders from Spotify feature teams to our finance organisation
This role will be based in Stockholm but will provide an opportunity for close collaboration with your New York colleagues.
What you will do
- Apply your expertise in quantitative analysis, data mining, and the presentation of data to help automate, optimise and understand key business problems and solutions
- Research, design, develop and evaluate highly innovative predictive models to understand the impact of specific behaviors, trends and patterns
- Work closely with cross-functional teams of data and backend engineers, analysts, user researchers, product managers and designers
- Build and analyze dashboards, reports to empower operational and exploratory data analysis
- Communicate insights and recommendations to key stakeholders, engineering and product partners
- Understand how user fraud affects other consumers of our data, including insights and feature teams, and work across the data landscape to minimise impact and drive influence wherever possible.
Who you are
- An MS/PhD in CS, Machine Learning, Operational research, Statistics or in a highly quantitative field. PhD strong plus.
- 3+ years of work experience in predictive modeling and data analysis
- You have a deep understanding of numbers, a strong interest in statistics and research, and an experienced and mature business sense.
- Strong analytical and problem solving ability
- Coding skills for analytics and data manipulation (SQL, R, Python, Pandas, Scala)Strong communication and data presentation skills (such as Tableau, Qlik, D3, ggplot)
- Experience performing analysis with large datasets in a cloud based-environment, preferably with an understanding of Google’s Cloud Platform
- Experience training and tuning statistical and machine learning models with libraries/frameworks such as sci-kit learn, tensorflow, pytorch or similar
- Familiarity with experimentation and A/B testing
- You are capable of tackling very loosely defined problems and thrive when working on a team which has autonomy in their day to day decisions.
- You are a communicative person that values building strong relationships with colleagues and multiple stakeholders, and have the ability to explain complex topics in simple terms.
- Ideally you have experience working at a large scale, global consumer product company, in a product analytics or insights role.
- Previous experience working in fraud detection and prevention, with an understanding of the impact that has on other areas in the company where business and product decisions are made.