Sr. Data Science Generalist

San Francisco / United States
Dev Team
Rainforest QA is an on-demand QA solution. It’s our mission to enable development teams to deliver bug-free software while moving at the speed of continuous delivery. Our headquarters are in the heart of San Francisco’s financial district but we are truly a global team, allowing us to bring together the best and most diverse talent. Our commitment to the distributed team model and to our company values has earned us multiple culture and workplace awards and helped us build a diverse team of individuals working toward the same goal: change the way QA is done.

Learn more about Rainforest QA by visiting our LinkedIn, Glassdoor, Instagram, and Facebook pages.

Data Science Generalist

What you’ll do

    • Experiment with the latest algorithms in computer vision, reinforcement learning and various supervised learning problems
    • Design, develop, and own ML products from brainstorming to speccing, implementation and maintenance
    • Research visual understanding of images, including classification, semantic segmentation, and OCR.  Develop new computer-vision based products with humans-in-the-loop
    • Ship improvements to existing products daily (we practice fast iterations and CI)
    • Work on fraud detection in crowdsourcing tasks
    • Dive into our tester management algorithms and look for ways you can improve them
    • Experiment with NLP to interpret our natural-language test cases
    • Develop a deep understanding of Rainforest products and empathy for our customers
    • Use your SQL and visualization skills to analyze and answer questions about our product and the way people use it

What we’re looking for

    • Knowledge of common data science concepts: different kinds of learning algorithms, ability to validate assumptions in a principled way and to discover correlations and to come up with a defensible experimental design to validate a hypothesis
    • Knowledge of Python including the scientific stack (numpy, scipy, matplotlib, pandas, scikit-learn etc.).
    • TensorFlow/Keras (though if you're already playing with PyTorch we'd gladly learn from you instead!)
    • Enough SQL to efficiently get the data you need from a relational DB
    • Basic knowledge of how the web works: HTTP, web servers, databases. Ability to build a simple CRUD app.
    • Comfort in using the Unix command line and git
    • Curiosity and motivation to think outside the box. When a colleague asks a data-related question, you're the type to try and understand what their underlying problem is and come up with a suitable solution (whether or not it can be solved with data).
    • Someone who stays up-to-date with the latest research in ML/AI, can chat about what they think the next breakthrough will be, and can point to a recent paper that they enjoyed reading

Bonus Points For:

    • First-hand experience with designing, building and shipping Deep Learning-based models to production

How we’ll reward you (SF)

    • Competitive compensation and stock options
    • 100% Medical, dental, and vision insurance covered (75% for dependents)
    • Daily catered lunch and snacks
    • Subsidized commuter benefits
    • Voluntary 401 k program
    • Generous vacation time
    • Professional development, in-office career coaching, and conference attendance
    • Dog friendly offices
    • Weekly team activities like happy hours, in-office yoga, and much more

How we’ll reward you (Remote)

    • Flexible, remote work options
    • Generous vacation time
    • Competitive compensation and stock options
    • Voluntary 401 k program (US only)
    • 100% Medical, dental, and vision insurance covered (US only, 75% for dependents)
    • Professional development, career coaching, and conference attendance
    • 3x per year onsites- we’ll fly you into our beautiful San Francisco office to spend quality time with your teammates!

At Rainforest QA we believe that diverse teams improve our business. We are an equal opportunity employer and do not discriminate on the basis of race, religion, color, nationality, gender, sexual orientation, age, marital status, veteran status, or disability status.