Data Scientist, Free ML
Compensation: $111,535.00 - $148,460.00 /year *
Employment Type: Full-Time
Industry: Information Technology
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Music for everyone, no credit card needed. It's a promise our platform was built on. And here in the Free team, we're still building on it. We work on a massive scale, bringing people from all kinds of disciplines and all parts of the business together to deliver an amazing freemium experience to more than 129 million users worldwide. Want to help shape the future of free? Here's how.
Spotify's Free Mission is the home of the team responsible for the success of Spotify's freemium business model that allows us to deliver an amazing free experience to more than 125 million users worldwide and deliver user-centered messaging to all 230 million+ users, both Free and Premium.
We're a team of technologists, product insight experts, designers, and product managers based in New York.
We are seeking a Data Scientist to join our Product Insights team, focusing on the development of our Machine Learning driven experiences and advertiser outcomes. You will help develop innovative solutions around the core problem of getting the right ad to the right user at the right time, while embodying Spotify's values and taking our users' best interest at heart.
What you'll do
* Perform analyses on large sets of data to extract actionable insights that will help drive ML driven product decisions
* Design and conduct A/B tests to drive iterative improvement to both user and advertiser metrics through efficient experimentation
* Communicate data-driven insights and recommendations to key stakeholders
* Work closely with cross-functional teams of ML engineers, user researchers, product owners and designers who are passionate about Spotify's success
* Build lasting solutions to surface critical data and performance metrics
* Help us develop our knowledge and practice around the development and evaluation ML driven products
* Develop individually to continue to grow your impact, and help mentor peers
Who you are
* You have at least 4+ years of experience in a similar data science role and a degree in science, computer science, statistics, economics, mathematics, or similar quantitative discipline.
* Ideally you have experience working in an analytics role working with ML functions and have conducted A/B tests, defined metrics and delivered exploratory analysis
* You have the technical competence to perform more advanced analytics:
* Coding skills for analytics and data extraction (SQL, R, Python, Pandas)
* Data visualization (such as Tableau, D3, ggplot, Looker)
* Experience performing analysis with large datasets
* Strong understanding of statistics and machine learning
* You are capable of tackling very loosely defined problems.
* You are a communicative person that values building strong relationships with colleagues and stakeholders and have the ability to explain complex topics in simple terms.
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 brilliant. 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 opportunity to enjoy and be inspired by 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 271 million users.
Associated topics: data analytic, data engineer, data management, data scientist, data warehouse, etl, hbase, mongo database, mongo database administrator, sql
* The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.
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