We are looking for a skilled and motivated data scientist with a focus on Natural Language Processing to join the Data Science team. This team embeds artificial intelligence and machine learning into our product portfolio and business to create coaching solutions and personalized experiences to help our users achieve success on their fitness journeys.
We encourage creative solutions and strive to maintain rigorous scientific and engineering standards.
What you’ll be doing:
Be a primary contributor to the design and implementation of our core NLP-powered products.In collaboration with our data scientists and senior engineers, you'll be introducing novel NLP-powered experiences, and driving innovation throughout the product using techniques such as Text Classification, Named Entity Recognition, Relation Extraction, and Attention-based models
Discover data sources, create and refine features from the underlying data
Perform hands-on data analysis and modeling with huge data sets
Apply data mining, NLP, deep learning, and machine learning (both supervised and unsupervised) to improve relevance and personalization algorithms
Work side-by-side with product managers, software engineers, and designers in designing experiments and minimum viable products
Explore new design or technology shifts in order to determine how they might connect with the customer benefits we wish to deliver
Qualifications to be successful in this role:
Strong background in implementing natural language processing, machine learning, and deep learning solutions
4+ years of industry experience with data science, including at least 2 years developing NLP and NN models
Experience with building and deploying services at scale
Experience working with Python, frameworks such as NLTK, spaCy, Keras, TensorFlow
Efficient in SQL, Hive, or SparkSQL, etc.
BS, MS, or PhD in an appropriate technology field (Computer Science, Statistics, Applied Math, etc.)
Solid communication skills: Demonstrated ability to explain complex technical issues to both technical and non-technical audiences