What You'll Be Doing
- Build machine learning solutions to solve various business questions.
- Perform ad-hoc exploratory statistics and data mining tasks on diverse datasets from small scale to big data
- Select features, build and optimize classifiers using machine learning techniques
- Perform data wrangling and feature engineering
- Data mining using state-of-the-art methods
- Extend company’s data with third party sources of information when needed
- Enhance data collection procedures to include information that is relevant for building analytic systems
- Process, cleanse, and verify the integrity of data used for analysis
- Carry out ad-hoc analysis and present results in a clear manner
- Maintain cutting edge in data science
- Take initiative in evaluating new approaches from data science research
- Test new tools, platforms and packages
- Support the programs for changing the business culture towards more data driven decision making
- Create helper functions to automate frequently encountered wrangling and feature engineering tasks
Skills You'll Need
- Masters or Bachelor Degree in Computer Science, Statistics, Applied Mathematics, Operations Research, or related majors.
- With industry experience in data science/machine learning projects working in a big data environment
- Industry experience in NLP, search, recommendation systems, time series modelling is a plus.
- Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, Random Forests, XgBoost etc.
- Familiar with sklearn
- Highly proficient with data wrangling and feature engineering
- Familiar with programming tools such as Spark, Python and SQL.
- Great communication and presentation skills
- Data-oriented personality and able to multi-task