Job Description :
Data Science@ Woodland Hills - CA

Location : Woodland Hills - CA

Job Description :

Skills Required : • Masters or PhD from a top-tier university with a specialization in Deep Learning, Machine Learning, Artificial Intelligence, Computer Vision, Statistics, Applied Math, Algorithm Design, or a related quantitative field • Healthcare domain knowledge • Able to invent and prototype novel machine learning algorithms from scratch • Expertise in automating and deploying models in production systems • Familiar with best practices for engineering in an enterprise environment • Proficient with programming languages like Python, R • Expertise with SQL databases • Expertise with Big Data and Hadoop tech stack (HDFS / Map Reduce / Mahout / Hive / Spark) • Strong written and spoken communication skills • Data visualization and communication skills including Statistics, data intuition and Wrangling No of Experience Expected: Senior profile (A minimum of 3 years’ hands-on applied or research experience developing machine learning models on large scale data sets) Job Description: Primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality analytical and prediction systems integrated with client’s healthcare platforms. Research and develop state-of-the-art machine learnings solutions to enhance business. Work closely with data and systems engineers to deploy and maintain models seamlessly on production systems. Establish scalable, automated processes for large scale data extraction, model development, model validation and model implementation. Effectively translate findings into actionable recommendations for senior leaders in business teams. Responsibilities: - Selecting features, building and optimizing classifiers using machine learning techniques - Data mining using state-of-the-art methods - Extending company’s data with third party sources of information when needed - Enhancing data collection procedures to include information that is relevant for building analytic systems - Processing, cleansing, and verifying the integrity of data used for analysis - Doing ad-hoc analysis and presenting results in a clear manner - Creating automated machine learning based systems and constant tracking of its performance