Data Scientist - XLabs - 193069
The person filling this position will be part of Experian APAC Data Lab concentrating on novel analytical solutions, new product prototyping, as well as new data asset evaluation and acquisition. This position requires extensive background and knowledge in machine learning and data science.
A successful candidate should also have previous experience in developing deep-learning algorithms and/or deep learning based analytic solutions using large datasets. Experience in the areas of optimization, symbolic AI, online marketing, experience in finance, insurance or healthcare is a plus.
The candidate will need to be able to work on multiple concurrent projects, anticipate obstacles, and make high quality deliveries on an aggressive schedule. The candidate must also be a team player that is self-motivated and has excellent communication skills. Key job functions include:
- Analyzing, processing, evaluating and documenting large data sets
- 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
- Developing data driven models to quantify the value of a given data set
- Applying, modifying and inventing algorithms to solve challenging business problems
- Validating score performance
- Conducting ROI and benefit analysis
- Documenting and presenting model process and model performance
- Advanced degree (PhD or Masters) in Machine Learning, Data Science, AI, Computer Science, Computer Engineering, Electrical Engineering, Physics, Statistics, Applied Math or other quantitative fields
- 0-3 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
- Proficient in deep learning (CNN, RNN, LSTM, attention models, etc.), machine learning (SVM, GLM, boosting, random forest, ), graph models, and/or, reinforcement learning
- Experience with open source tools for deep learning and machine learning technology such as Keras, tensorflow, pytorch, 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
- Extensive knowledge of Python and related libraries
- Experience with Hadoop and NoSQL related technologies such as Map Reduce, Spark, Hive, HBase, mongoDB, Cassandra, etc.
- Experience with online, mobile marketing analytics
- Experience with GPU programming
- Experience with Natural Language Processing, Natural Language Understanding, and the relevant open-source tools
- Solid knowledge of Bayesian statistical inference and related machine learning methods
- Experience with Agile methods for software development