IICS Technical Specialist

Responsibilities

• Performs the code development of complex analytic algorithms and paradigms.
• Performs a clear breakdown of the analytic functionality and separates it into working modules.
• Selects the appropriate modeling technique and/or technology with consideration to data limitations, application, and business needs.
• Builds session-level models and analyzes high-volume clickstream data from digital platforms.
• Develops sequence modeling using RNN, Transformers, LSTM, XG Boost, Decision trees, Bayesian networks, Random forest, Logistic regression, Support vector machine, Gradient boosting algorithms, Clustering algorithms, and Dimensionality Reduction Algorithms.
• Develops Deep Learning models using TensorFlow, Keras, and PyTorch.
• Hands-on experience in building ML workflows.
• Fluent with Natural Language Processing and Text Analytics libraries (NLTK, SpaCy).
• Experience in Model implementation, governance, and monitoring.

Requirements

• Proven experience in developing sequence modeling using RNN, Transformers, LSTM, XG Boost, Decision trees, Bayesian networks, Random forest, Logistic regression, Support vector machine, Gradient boosting algorithms, Clustering algorithms, and Dimensionality Reduction Algorithms.
• Experience in Deep Learning model development using Tensorflow, Keras, PyTorch.
• Experience in building ML workflows.
• Fluent with Natural Language Processing and Text Analytics libraries (NLTK, SpaCy).
• Experience in Model implementation, governance, and monitoring.
• Experience with Python, R, and SQL.
• Experience with Python data science packages such as NumPy, SciPy, and SciKit-Learn.
• Hands-on experience in building ML workflows.
• Experience with one of Subversion/SVN, Git, GitHub, GitLab, Mercurial, or other version control systems.
• Experience with cloud platforms AWS, Azure, GCP.
• Knowledge in Big Data, Hadoop, HIVE/HQL, HDFS, Spark/PySpark, Kafka.

Qualifications

• Bachelor's degree or Master's Degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, Engineering etc.) or equivalent experience.
• Minimum 8-10 years of experience in data science and advanced analytics.

Skills

• Python
• R
• SQL
• Data Science Platforms (Dataiku, H2o, Azure)
• Version Control Systems (Subversion/SVN, Git, GitHub, GitLab, Mercurial)
• Cloud Platforms (AWS, Azure, GCP)
• Big Data Technologies (Hadoop, HIVE/HQL, HDFS, Spark/PySpark, Kafka)

Benefits

Nice to have experience with Data Science Platforms (Dataiku, H2o, Azure) and knowledge in Big Data, Hadoop, HIVE/HQL, HDFS, Spark/PySpark, Kafka.

Pay

The expected pay range for this contract assignment is shown above with the Job details.

Schedule

The exact pay rate will vary based on skills, experience, and location and will be determined by the third-party employer.