Vacancy expired!
- Selecting features, building and optimizing classifiers using machine learning techniques to enhance predictive analytics.
- Neural Networks 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.
- Excellent understanding of machine learning and neural networks techniques and algorithms, such as CNNs, Transformer Networks, SVM, Decision Forests, etc.
- Experience with common data science toolkits, such as Sci-kit Learn, Spark ML, PyTorch, Keras, etc. Excellence in at least one of these is highly desirable
- Experience with data visualization tools, such as Tableau, Matplotlib, etc.
- Proficiency in using query languages such as SQL or equivalent
- Proficiency with Excel in terms of analyzing data and producing graphs, tables, and reports.
- Good, applied statistics skills, such as distributions, statistical testing, regression, Bayesian, Markov chains, etc.
- Good scripting and programming skills in R, Python, Java, or equivalent
- Data-oriented personality
- Proficiency with SQL and NoSQL databases
- Good scripting and programming skills in Python, Java, or equivalent
- Knowledge of operating systems such as Windows, Linux, UNIX, or equivalent
- Proficiency of data engineering tools such as Redshift, Bigtable, AWS Athena, or equivalent
- Basic understanding of machine learning and statistical analysis
- Experience with data analysis solutions/tools such as ETL, MapReduce, Hive, Data APIs, or equivalent
- Proficiency with Excel in terms of analyzing data and producing graphs, tables, and reports.
- PhD degree in Statistics, Operations Research, EE, CS or equivalent / related area
- 2+ years of experience in data analytics.
Vacancy expired!