909 North Sepulveda Blvd
Job Category: Big Data
Job Number: 18667
- 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
- Processing, cleansing, and verifying the integrity of data used for analysis.
- Doing ad-hoc analysis and presenting results in a clear manner
- Apply machine learning, collaborative filtering, NLP, and deep learning methods to massive data sets
- Collaborate with cross-functional agile teams of software engineers, domain experts, and others to build new product features for multiple business units of the company
- Collaborate with data scientists across a variety of businesses to prioritize and promote the company’ s machine learning efforts
Skills and Qualifications:
- B.S., M.S. or PhD in Computer Science, Software Engineering, Information Science, Mathematics, Statistics, Electrical Engineering, Physics or related fields or equivalent experience.
- Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
- Experience with common data science toolkits, such as R, Scikit-learn, NumPy, TensorFlow
- Strong knowledge in POS tagger, shallow and deep parser, feature scaling, dimensionality reduction & data compression techniques, TF-IDF, SVM, Ensemble models (Bagging, Boosting), model tuning using grid-search etc.
- 5+ years of software development experience in NLP development & or text analytics.
- 5+ years of experience implementing machine learning systems at scale in Python (preferred), Scala, or Java.
- You care about agile software processes, data-driven development, reliability, and responsible experimentation.
- You preferably have machine learning publications or work on open source to share with us.
- Excellence in at least one of these is highly desirable:
- Experience with data visualization tools, such as D3.js, GGplot, etc.
- Proficiency in using query languages such as SQL.
- Experience with NoSQL databases.
- Experience with data processing and storage frameworks like Hadoop, Spark, Kafka, etc.