Job Summary

Your primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with our products.

  • Minimum Qualification: Bachelor
  • Experience Level: Entry level
  • Experience Length: 1 year

Job Description

DEPARTMENT: INFORMATION TECHNOLOGY

A data scientist will help the company discover the information hidden in vast amounts of data, and help us to make smarter decisions to deliver even better products. 


REPORTS TO: Chief Information Technology Officer.


KEY RELATIONSHIPS

  • Internal – IT team members and Senior Management staff.
  • External – Key client contact persons.


WHAT WORK WILL BE DONE IN YOUR ROLE

  • Innovation Work: To be agreed with the supervisor
  • Improvement Work: To be discussed and agreed with supervisor


DUTIES & RESPONSIBILITIES

  1. Selecting features, building and optimizing classifiers using machine learning techniques
  2. Data mining using state-of-the-art methods.
  3. Extending company’s data with third party sources of information when needed.
  4. Enhancing data collection procedures to include information that is relevant for building analytic systems.
  5. Processing, cleansing, and verifying the integrity of data used for analysis.
  6. Doing ad-hoc analysis and presenting results in a clear manner.
  7. Creating automated anomaly detection systems and constant tracking of its performance.


COMPETENCIES, SKILLS, QUALIFICATIONS, EDUCATION & EXPERIENCE

Competencies:

  • 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.
  • Proven ability to work independently on development of complex models with extremely large and complex data structures.

Skills:

  • 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.
  • Proficient in more than one of Python, R, Java, C++, or C.
  • Experience in large data analysis using Spark.
  • Robust knowledge and experience with statistical methods.

Education, Qualifications & Experience:

  • Bachelor’s Degree in Data Science, AI, Computer Science, Computer Engineering, Statistics, Applied Math or other quantitative fields required.
  • 1-3 years of working experience in data science, and/or predictive modeling.

Pluses:

  • Extensive knowledge of MATLAB and SQL.
  • Experience with Hadoop and NoSQL related technologies such as Map Reduce, Spark, Hive, HBase, mongoDB, Cassandra, etc.
  • 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.

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