Data Science Intern at Demandbase

Introduction to Demandbase: 
Demandbase is the Smarter GTM™ company for B2B brands. We help marketing and sales teams overcome the disruptive data and technology fragmentation that inhibits insight and forces them to spam their prospects. We do this by injecting Account Intelligence into every step of the buyer journey, wherever our clients interact with customers, and by helping them orchestrate every action across systems and channels - through advertising, account-based experience, and sales motions. The result? You spot opportunities earlier, engage with them more intelligently, and close deals faster. 
As a company, we’re as committed to growing careers as we are to building world-class technology. We invest heavily in people, our culture, and the community around us. We have offices in the San Francisco Bay Area, New York, Seattle, and teams in the UK and India, and allow employees to work remotely. We have also been continuously recognized as one of the best places to work in the San Francisco Bay Area.
We're committed to attracting, developing, retaining, and promoting a diverse workforce. By ensuring that every Demandbase employee is able to bring a diversity of talents to work, we're increasingly capable of living out our mission to transform how B2B goes to market. We encourage people from historically underrepresented backgrounds and all walks of life to apply. Come grow with us at Demandbase!
About the Data Science Team:
You will be a member of Demandbase’s Central Data Science team that drives product innovation and is responsible for all ML/AI initiatives and projects. We build and apply ML models at every stage of the B2B buyer’s journey. Starting from the top of the funnel, Data Scientists build account rank models to score tens of millions of companies and also recommend companies that aren’t yet in their CRM. Our Data Scientists apply cutting-edge natural language processing algorithms and deep learning models to predict whether a company is interested in our clients' products even before they visit their site. Once ML-generated account lists are built, we launch campaigns to generate awareness and traffic to target sites.  
Our Data Scientists build pacing, pricing, click-through rate, and engagement models using tens of billions of auctions daily to optimize campaign performance. We build reinforcement learning algorithms to optimize the user experience when potential prospects click on ads/banners and visit our customers’ websites.  
Our Data Scientists build real-time intent using time series analysis to trigger an alert for sales after potential prospects share their contact information, to contact prospects when there’s an intent surge. ML models are a significant differentiator for each of our offerings in the ABM platform, Targeting, Conversion, and Intent products.  Our Data Scientists not only build ML models, but are also substantially involved in productizing the models, and working closely and cross-functionally with data engineering, application, product, and UX design teams to deliver the world’s best account-based marketing and advertising product.
Below are examples of some of the types of projects you can expect to work on:

Identification and account intelligence: map billions of IPs and cookies to companies 
Rank accounts in B2B buying journey 
Intent: develop a browsable taxonomy of intent signals

What you'll be doing:

Help develop Machine Learning algorithms that optimize and make an immediate business impact on KPIs. 
Build, test, and deploy custom ML/AI models and algorithms on large datasets, and develop processes for monitoring and analyzing their performance in production environments. 
Communicate algorithms, complex data science methods, and statistical results with technical and non-technical audiences.
Stay current with the latest technology/research and drive innovation. 

What we're looking for:

Current students or those who have graduated within the past year are encouraged to apply
Background in Statistics, Computer Science, Machine Learning, Mathematics, Computational Psychology, Operational Research, Physics, or relevant field
Driven more than one greenfield project from concept to production release
Proficiency with analytical and database tools (e.g. Jupyter notebooks, Hive, SQL, No-SQL)
Demonstrated ability to write clean and performant code in Python
Depending on the project you work on, experience with 1 or more of these AI/ML technologies: TensorFlow, scikit-learn, Spark MLlib, Bigquery Machine Learning, large-scale data sets, Natural Language Processing and Graph algorithms.
Able to break down complex problems and come up with simple innovative solutions
Data is your thing, you love metrics and use metrics to drive projects