Data Scientist

Company:
Location: San Diego, CA 92130

*** Mention DataYoshi when applying ***

About us, but we’ll be brief

We are thrilled to share that FORTUNE has named Experian one of the 100 Best Companies to Work For. In addition, for the last five years we’ve been name in the top 100 “World’s Most Innovative Companies” by Forbes Magazine.


Experian DataLabs is a R&D unit at Experian formed with the desire to work in collaboration with Experian’s business units to enhance relationships with clients and acquire strategic datasets. Experian® is a global leader in providing information, analytical tools and marketing services to organizations and consumers to help manage the risk and reward of commercial and financial decisions. Using our comprehensive understanding of individuals, markets and economies, we help organizations find, develop and manage customer relationships to make their businesses more profitable.


What you’ll be doing

You will be part of Experian North America R&D DataLabs concentrating on research and development of novel analytical solutions, new product prototyping, as well as new data asset evaluation and acquisition. This position requires extensive background and knowledge in deep learning and machine learning. The key job functions include:

  • Develop complex machine learning-based analytical solutions extracting insights from large amount of structured and unstructured data from diverse data sources
  • Identify/develop appropriate machine learning/deep learning/natural language understanding/natural language processing techniques to uncover the value of the data
  • Designing data structure and data storage schemes for efficient data manipulation and information retrieval
  • Developing tools for data processing and information retrieval
  • Analyzing, processing, evaluating and documenting large data sets
  • Applying, developing and inventing algorithms to solve challenging business problems
  • Validating score performance and conducting ROI and benefit analysis
  • Documenting and presenting model process and model performance

What your background looks like

  • Advanced degree in Machine Learning, Data Science, AI, Computer Science, Computer Engineering, Electrical Engineering, Physics, Statistics, Applied Math or other quantitative fields
  • 0-6 years of working experience in data science, and/or predictive modeling
  • Demonstrated ability to lead and execute projects from start to finish
  • Ability to independently support existing products
  • Proven track record in modifying and applying advanced algorithms to address practical problems
  • Experience in deep learning (CNN, RNN, LSTM, attention models, etc.), machine learning (SVM, GLM, boosting, random forest, etc.), graph models, and/or, reinforcement learning.
  • Experience with generative modeling techniques such as GAN
  • Experience with open source tools for deep learning and machine learning technology such as pytorch, Keras, tensorflow, scikit-learn, pandas, etc.
  • Proven ability to work independently on development of complex models with extremely large and complex data structures
  • Proficient in more than one of Python, R, Java, C++, or C
  • Experience in large data analysis using Spark (pySpark preferred)
  • Robust knowledge and experience with statistical methods

Plusses:

  • Experience with Natural Language Processing, Natural Language Understanding, and the relevant open-source tools
  • Experience in developing, modifying and experimenting advanced language models
  • Experience in developing/applying/evaluating conversational AI technology
  • Extensive knowledge of SQL
  • Experience with Hadoop and NoSQL related technologies such as Map Reduce, Hive, HBase, mongoDB, Cassandra, etc.
  • Experience with online, mobile marketing analytics
  • Experience with GPU programming
  • Solid knowledge of Bayesian statistical inference and related machine learning methods.
  • Experience with Agile methods for software development

EOE including Disability/Veteran

*** Mention DataYoshi when applying ***

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