- Work on data parsing, analyzing, investigating, interpreting, modeling, and extracting knowledge from large volumes of data.
- Process data to help drive better business decisions in a fast-paced environment
- Extract data from databases, write scripts to parse, clean, combine, and process them
- Draw inferences and conclusions, communicate results through reports, charts, or tables
- Use predictive analytics and machine learning to create new products or drive business decisions
- Design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience
- Investigate data problems, identify patterns
- Create dashboards and visualizations of processed data, identify trends, anomalies
Your Skills and Experience
- Ph.D. or Master Degree in Computer Science, Applied Statistics, Mathematics or a related Quantitative Discipline.
- Minimum 5 years of experience on a development team, shipping production software.
- Agile software development practice.
- At least 3 years of experience with Spring Java. MongoDB experience is also required
- Data Mining and Machine learning experience including:
- Solid understanding and experience in applying and implementing machine learning algorithms and concepts such as: K-means Clustering (varieties), Gaussian distribution, decision tree, boosting, etc.
- Experience working with BigData and Machine learning analytics tools such as: R, Neo4J, MADlib, Spark, Hadoop MapReduce.
- Experience with REST based API development and JSON data formats.
Why You'll Love Working Here
What we offer:
- Young, open and dynamic, fast-growing yet professional working environment with talented, high passionate colleagues.
- Very competitive package as compared to the market. 100% salary since probation.
- 100% company-sponsored training budget, study English or professional courses, certificates as much as possible.
- Excellent benefit program: 13th salary guarantied, premium healthcare insurance program, transportation allowance, extra holiday.
- Bi-weekly team building parties, Company trips, charity activities
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