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