Quick overview
SeniorityMid Senior
Work modeOn Site
LocationSan Diego, CA, United States
SQLETLNLPScikit-learnDeep LearningHivePythonMachine LearningData Analysis
Job description
Role: Data Scientist
Location: Oakland/MTV/San Diego CA (3 days Work from Office)
Persistent systems
Responsibilities
- Perform hands-on data analysis and modeling with huge data sets
- Apply data mining, NLP, and supervised/unsupervised ML to design, improve, and evaluate relevance and personalization algorithms across customer journeys.
- Work side-by-side with product managers, software engineers, and designers in designing experiments and minimum viable products
- Discover data sources, get access to them, import them, clean them up, and make them “model-ready”. You need to be willing and able to do your own ETL
- Engineer and iterate on features from underlying data, combining domain understanding with statistical rigor to propose, evaluate, and refine feature sets that improve model performance over successive cycles.
- Run regular A/B tests, gather data, perform statistical analysis, draw conclusions on the impact of your optimizations and communicate results to peers and leaders
- Explore new design or technology shifts in order to determine how they might connect with the customer benefits we wish to deliver
Qualifications:
- BS, MS, or PhD in an appropriate technology field (Computer Science, Statistics, Applied Math, Operations Research, etc.)
- 4+ years of industry experience with Data Science and Machine Learning
- 4+ years of experience in modern advanced analytical tools, programming languages - Python with scikit-learn
- Efficient in SQL, Hive, SparkSQL, etc.
- 4+ years of experience in applied machine learning and statistical modeling (e.g., classification, regression, decision trees, neural networks, recommender systems, sequential pattern discovery, and text mining), with hands-on experience in deep learning and embedding-based representations for NLP/language understanding, recommendation, and personalization.
- Solid communication skills: Demonstrated ability to explain complex technical issues to both technical and non-technical audiences
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