Principal Data Scientist ? Personalization ? Telecommute

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Join our Personalization Team, as a Principal Data Scientist, which works on solving recommendations, ranking, user condition predictions, and search problems. We are KPIs driven team that leverages Machine Learning (ML) to provide a personalized experience. In this team, you would work with brilliant data scientists and engineers to build end-to-end solutions to meet product needs. We are also very passionate about our engineering excellence and pride ourselves of releasing solid solutions to production. We leverage state of art machine learning and strive for low latency solutions.

You’ll enjoy the flexibility to telecommute* from anywhere within the U.S. as you take on some tough challenges.

Primary Responsibilities:

• Apply advanced statistical and predictive modeling techniques to data related to the optimization of healthcare and digital experiences
• Propose innovative ways to look at problems using data mining, statistical analysis and machine learning
• Communicate findings, verbally and visually, to business partners and clients
• Seek out new data sources and verify integrity of data that fill gaps and improve models
• Support business needs around analytics, predictive modeling and business intelligence
• Collaborate effectively with internal clients, transforming their needs into data science use cases
• Provide on-going tracking and monitoring of performance of statistical models and recommend ongoing improvements to methods and algorithms

You’ll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

Required Qualifications:

• Master’s degree in Computer Science, Applied Mathematics, (Bio) Statistics, Applied Statistics, Economics, or similar quantitative fields of study
• Ability to turn state-of-art research into production level codes
• Experience in developing analytics with machine learning, deep learning, NLP, and/or other related modeling techniques
• Experience in python, Tensorflow, Pytorch and/or Pyspark
• Ability to translate business need and requirements into technical solutions
• Solid analytical and problem-solving skills

Preferred Qualifications:

• Ph.D. degree in Computer Science, Applied Mathematics, (Bio) Statistics, Applied Statistics, Economics, or similar quantitative fields of study
• Experience in developing and deploying models related to recommender system, NLP and time series forecasting
• Experience in developing algorithms for search engines (e.g. name entity recognition, intent classification, spell correction, autocompletion), cold-start recommendation, semi-supervised learning (e.g. positive unlabeled learning)