Graduating students encouraged to apply (Masters/PHDs would be an advantage)
The individual MUST have proven track record (or at least possessing such capability or knowledge) of industrial implementation of various categories of work inclusive of however not limited to building a large scale recommendation system, time-series predictions (Economics, Stock Markets, Machines, etc), optimization (Genetic Algorithms, Simulated Annealing, etc), statistical analysis and modeling. Knowing image processing is a plus. Experience with formulating or implementing algorithms that are capable of evolution (automated parameters updating) would be of a great advantage.
Large data sets should excite this person
A strong knowledge of statistics and data analysis with experience in machine learning techniques (supervised and unsupervised learning), time series analysis, and experiment design
Strong analytical skills and facility with Excel (pivot tables, lookups, formulas, formatting)
SQL knowledge a must
Experience with statistical software (Matlab, SPSS, SAS, R) and Hadoop a plus
.Net, Java, HTML 5, Python, HiveQL knowledge a plus
Knowledge in Machine Learning/ “R” programming / Python is an added advantage.
A desire to learn new methods in data mining/manipulation
Background in statistics, software engineering, data mining, database administration, or other quantitative disciplines is highly valued
Ideally an all-rounded person whose related knowledge is more profound than our in-house experts combined.
Candidate will have to undergo screening test (theoretical and practical) during the interview which topics are Statistics, Machine Learning, Programming and Apache modules.
The individual should have a desire for data mining, scripting, problem solving and statistical analysis.
The individual will be responsible for scripting data models, automating data feeds, using BI tools to help visualize data, and various ad hoc projects.
The individual will also need to drive statistical analysis projects from beginning to end, and have working experience with regression, factor analysis, building models and predictive analytics.
Strong communication skills to obtain stakeholder buy-in and convince audience on the quality of the delivered models are critical to this position.
To work collaboratively with DBAs, data scientists, and analysts.
Drive improvement in our methodologies, systems and processes
Have a deep understanding of large data, our data structures, and how to manipulate our data in an efficient manner
Have working experience with statistical tools such as R and Python (SciPy and other relevant packages),SPSS, SAS, have the ability to create statistical models, analyze factors significant to driving user engagement and build predictive models based on historical data
Have working experience with Machine Learning (supervised learning, unsupervised learning, semi-supervised learning, graphical models, image processing, reinforcement learning, reproducing kernel hilbert space).
Quick in formulating quality, feasible and practical solution fit to big data (usually) application .