Data Scientist

Data Scientist

This job is no longer open

Udacity's mission is to power careers through tech education. Our immersive online learning platform offers practitioner-level training in fields such as Artificial Intelligence, Machine Learning, Data Science, Autonomous Systems, Cloud Computing and more. Backed by well-known investors such as Andreessen Horowitz, Charles River Ventures, Bertelsmann and Drive Capital, Udacity is transforming the world by providing life-long learners the opportunity to upskill in bleeding edge career fields. We also partner with leading enterprises to support them on their journey of digital transformation for their workforces. If you are inspired to be part of something amazing…read on!

We use machine learning to help users achieve their learning goals, from first engagement through our lifetime relationship. We are looking for a Data Scientist to help revolutionize Udacity's online learning platform by using Machine learning techniques including Deep Learning, Natural Language Processing, Recommendation Systems, and Computer Vision. You will be a key part of a growing and dynamic data team that works daily with strategic stakeholders to develop predictive models and algorithms to power data products. This is a chance to affect thousands of students around the world who come to Udacity to improve their lives, and your success as part of a world-class data organization will be visible up to the highest levels of the company.

Responsibilities:

  • You will report to Sr. Manager of Data (based in California, USA) and be a team member on Udacity’s emerging data science team where you will be developing predictive models and algorithms to power data products.
  • You will operate with end-to-end ownership, which includes own the analysis, modeling, system design, and development of the data product
  • Address machine learning problems around recommendation engines, personalization, and other classification/regression problems.
  • Solve problems related to discovering user preferences efficiently and delivering personalized experiences.
  • Experiment and build new algorithmic capabilities from the ground up. 
  • Contribute to building out Udacity’s machine learning platform - with the aim of bringing together various open-source and in-house tools to streamline ML workflows. 
  • Integrate disparate production systems to make your model work in real-time applications.

What we value:

  • 5+ years of experience in data science, analytics, statistics, or engineering
  • You have advanced programming experience (Python, R, SAS, Matlab)
  • You have advanced database knowledge (SQL, Redshift, Postgres, Presto)
  • Experience with machine learning frameworks including scikit-learn, TensorFlow and Pytorch
  • Experience deploying machine learning models into production.
  • You have strong cross-functional communication skills that help simplify and move complex problems forward with business partners

Preferred Experience:

  • Degree in a quantitative field such as Computer Science, Statistics, Physics, or a related field.
  • Knowledge of Deep Learning, Natural Language Processing, Reinforcement Learning or Self Learning
  • Experience deploying machine learning models with AWS SageMaker
  • Experience deploying ETLs with Airflow and/or Spark
  • Knowledge of proper A/B testing practices and statistical experiment design
  • You are excited to ask questions, push boundaries and follow where data leads in pursuit of new opportunities
  • You are a curious self-starter, driven to solve problems and find answers. You take charge and flourish when meeting a challenge and you do not shy away from potential failure.

Consider applying if your experience is close to what we described above. We look for people with exceptional potential, as we know highest performing teams include people of diverse backgrounds, perspectives, and life experiences.

Udacity is proud to be an Equal Employment Opportunity employer. We believe that the unique contributions of all Udacians is the driver of our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience we never discriminate on the basis of regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

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