Range of years of experience: 5+ years of experience in an enterprise data science role for standard
Skills:
University degree in mathematics, statistics, machine learning, data science or related field.
* Expert knowledge of Python and related ML packages.
* Expert knowledge of clustering and classification methods and strategies.
* Knowledge of Natural Language Processing tools and techniques.
* Experience with web analytics tools and techniques.
« Experience with data visualization tools and methods.
Experience with cloud platforms and architecture (Big Data, Cloud ML).
Knowledge of CI/CD tools and procedures.
* Knowledge of provisioning of data APIs.
Proven ability to communicate with business experts and present ML results.
Software development languages and tools: Python, Jupyter, SQL, Tableau, AWS, QuickSight, Athena, Glue, Spark
Project objectives:
This role focuses on enhancing the existing digital analytics and name harmonization use cases
built upon the Enterprise Analytics Platform. It seeks to augment existing services by strategically
applying data science techniques, while ensuring customer privacy and security.
The Data Science Specialist is primarily responsible for using statistics, data mining and predictive &
modelling techniques to gain insights, predict behaviors, and generate value from customer data. go
The Data Science Specialist works within the Information and Communication Technology
Department, under the supervision of the IP Portal Senior Data Scientist.
Tasks:
The Data Science Specialist provides the required expertise to design and deploy data products in
the Enterprise Analytics Platform, using an interactive/agile approach.
(a) Provide time sensitive analyses on various customer and business questions.
(b) Use Natural Language Processing to establish relationships between multiple datasets.
(c) Perform clustering and classification analysis on large datasets.
(d) Identify and address privacy and confidentiality concerns. Collaborate with the
establishment of data-handling practices to ensure the Organization’s information
security guidelines are followed.
(e) Prepare reproducible analyses using data science notebooks.
(f) Use multiple statistical and machine learning methods to build and derive value from
customer graphs.
(g) Establish model drift monitoring strategies.